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For example: .example { color: red; } For brushing up on your CSS knowledge, check out http://www.w3schools.com/css/css_syntax.asp End of comment */ .envira-tags-filter-active{ border-radius: 0!important; background-color: transparent!important; color: black!important!important; border: 4px solid black!important; PADDING: 10PX 20PX!important;} .envira-tags-filter-link{ border-radius: 0!important; background-color: transparent!important; color: black!important; } .envira-tags-filter-list{ display: table!important; margin: 0 auto!important; padding-bottom: 40px!important;} .filters.rounded .sort { padding: 3px 20px; color: black!important; font-size: 18px; } .filters.rounded .current_choice { border-radius: 0!important; background-color: transparent!important; color: black!important; border: 4px solid black!important; } #portdark .thumb-wrap{pointer-events:none!important; cursor:normal!important}</style>   <style type="text/css"> /* Add your CSS code here. For example: .example { color: red; } For brushing up on your CSS knowledge, check out http://www.w3schools.com/css/css_syntax.asp End of comment */ #tree-container { display: flex; justify-content: center; } .node { cursor: pointer; } .overlay { background-color: black!important; } .node circle { stroke: steelblue; stroke-width: 1.5px; } .node text { font-size: 14px; font-family: sans-serif; } .link { fill: none; } div.tooltip { position: absolute; padding: 10px 15px; font: 12px sans-serif; background: lightsteelblue; border: 0px; border-radius: 8px; z-index: 1; box-shadow: 0 5px 10px rgba(0,0,0,0.2); } div.tooltip:empty { padding: 0; } div.tooltip p { margin: 5px 0 0; } </style>   <style type="text/css"> /* Add your CSS code here. 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} .awsm-personal-info h3{margin-bottom: 10px!important;} figcaption .awsm-personal-info{ border-bottom:none!important;} .awsm-personal-info{ padding-top: 20px; border-bottom: 1px solid black; padding-bottom: 15px;} .awsm-personal-info .comptit, .jobpos{ text-transform: uppercase; font-size: .9em; line-height: 1.9; display: block; color: black; } .jobpos{ font-style: italic;} #page-content h3{ font-family: Roboto; font-weight: 300;} p span, .tatsu-button-wrap a{ font-family: Roboto; font-weight: 300;} h5 span, h4{font-family: Roboto!important;} h2 span, .tatsu-text-inner, p, span, strong, h1, h2, h3, h4, h5 {font-family: Roboto!important;} h3{font-weight:700!important} #page-content li{font-family: Roboto!important; } .single-post .hero-section-wrap{height:400px;} .style1-blog .article-details, .style5-blog .article-details, .style6-blog .article-details { padding: 0px 0 0!important; } .single-post .content{padding-top:40px!important;} .single-post .tagcloud{display:none!important;} .post-template-default #header-wrap{display:block!important;} .post-title a{ font: 700 55px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 70px; letter-spacing: 0px; text-transform: none;} .style2-blog .post-nav, .style3-blog .post-nav, .style5-blog .post-nav, .style6-blog .post-nav{ display:none!important; } .single-post .section-overlay{ opacity: 0.5!important;} .single-post select{ width: 99%!important;} .single-post .hbspt-form input[type="text"]{ width: 95%!important;} .single-post .stacked .actions { margin-left: 0!important;margin-top:0px!important;padding-top:0px!important} .single-post .hs-button { display: table!important; margin: 0 auto!important; } .single-post .hbspt-form input[type="text"] { padding-bottom: 0px; width: 95%!important; } .single-post .hs-field-desc { width: 100%; color: #aaa; margin: 0px 0px 5px 150px; font-size: 11px; font-family: "Helvetica Neue",Helvetica,Arial,sans-serif; line-height: 15px; text-align: center; } .single-post .hs-form-required{display:none!important;} .single-post .hbspt-form { border: 1px solid #1fbdef!important; padding: 10px; } .single-post .hs-input {margin-bottom:0px!important} .single-post .hs-richtext h5 { font-family: Open Sans, Arial, sans-serif; font-size: 20px; text-align: center; color: #1fbdef; } #navigation-left-side { padding-right: 90px; } #navigation-right-side { padding-left: 90px; } #navigation-left-side a, #navigation-right-side a, #navigation a { padding: 0 10px!important;} .ui-accordion .ui-accordion-header.ui-state-active { background: #2CB5E9!important; } .ui-accordion .ui-accordion-header.ui-state-default { background: #428BCA; } body .ui-accordion .ui-accordion-header { margin-top: 1px; } body .ui-accordion .ui-accordion-header { padding: 14px 18px; color: #fff; font-size: 18px; } body .ui-accordion-header-icon.ui-icon.ui-icon-triangle-1-s, body .ui-accordion .ui-accordion-header.ui-state-active:hover .ui-accordion-header-icon.ui-icon.ui-icon-triangle-1-s { width: 24px; height: 24px; float: right!important; background: url(https://staging6.odsc.com/wp-content/themes/oshin/images/rounded_arrow_up.png) no-repeat center center transparent; } body .ui-accordion .ui-accordion-header .ui-accordion-header-icon { position: relative; left: auto; right: auto; top: 0; margin-top: 0; } .ui-icon.ui-icon-triangle-1-e, .ui-accordion .ui-accordion-header.ui-state-default:hover .ui-icon.ui-icon-triangle-1-e { width: 24px; height: 24px; float: right; background: url(https://staging6.odsc.com/wp-content/themes/oshin/images/rounded_arrow.png) no-repeat center center transparent; } .svg_container.big.handshake img { max-width: none; width: 56px; } p.date { color: #15c2e0; font-weight: bold; text-transform: uppercase; margin-bottom: 0; } .svg_container.big.handshake { padding: 25px 30px 20px 15px; } .svg_container.blue, .blue .svg_container { background: rgba(0, 188, 221, 0.32); } .svg_container.big { padding: 20px; width: 40px; height: 40px; } .svg_container { width: 28px; height: 28px; float: left; padding: 14px; margin-top: 0; margin-right: 14px; border-radius: 50%; }</style>   <style type="text/css"> /* Add your CSS code here. For example: .example { color: red; } For brushing up on your CSS knowledge, check out http://www.w3schools.com/css/css_syntax.asp End of comment */ #ptsTableInitEditHtmlDlg{width:100%!important} #odsc-tickets .groups__group { } @media only screen and (max-width: 960px){ body.sticky-header #header #header-inner-wrap.no-transparent { position: fixed!important; left: 0!important; right: 0 !important; top: 0px !important; }} .kolumnspec select { width: 100%!important; font: 400 18px "Source Sans Pro","Open Sans","Arial",sans-serif!important; border:none!important; height:41px!important; } .newslee input[type="email"]{ width: 100%!important;} .kolumnspec ul { list-style: none!important; } #odsc-tickets .groups__group:hover { background: #f7f5f5; } /* Timetable */ @media only screen and (min-width: 992px){ .tcode-event-schedule .scheduled-event .artist-image { height: 92px; width: 92px; } } .artist-image .img-responsive{border-radius: 50%;} @media only screen and (max-width: 767px){ .klasicc .tatsu-eq-cols .tatsu-column { min-height: 270px!important; } } /*register page*/ @media only screen and (max-width: 460px) { .fixe span{line-height:55px;} } .mobmenu{display:none!important;} .mobmenu-push-wrap, body.mob-menu-slideout-over { padding-top: 0px!important; } @media only screen and (max-width: 964px) { .page-id-161 #header-inner-wrap{ /* display:none!important;*/ } .page-id-161 .mobmenu{display:block!important;} .page-id-161 .mobmenu-push-wrap, .page-id-161 body.mob-menu-slideout-over { padding-top: 40px!important; } } .mptt-shortcode-wrapper .mptt-shortcode-table{ color: white; } .mptt-shortcode-wrapper .mptt-shortcode-table tr.mptt-shortcode-row th{ background-color: transparent; color: white; padding: 1rem; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody tr:nth-child(2n+2) { background-color: transparent; } .mptt-shortcode-wrapper .mptt-shortcode-table.mptt-theme-mode tbody td.event{ background-color: transparent; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody div[data-color="#48AFDE"] .event-subtitle, .mptt-shortcode-wrapper .mptt-shortcode-table tbody div[data-color="#48AFDE"] .timeslot{ color: white !important; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody .mptt-shortcode-event.mptt-event-vertical-top[colspan="4"] .mptt-event-container{ background-color: transparent !important; justify-content: center; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody .mptt-event-container .event-title{ font-weight: bold; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody [colspan="4"] .event-title{ font-size: 24px; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody .mptt-event-container:hover .event-title{ text-decoration: none !important; } .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17418"] .mptt-event-container, .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17423"] .mptt-event-container{ background-color: rgba(105, 217, 226, 0.15); } .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17418"] .mptt-event-container:hover, .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17423"] .mptt-event-container:hover{ background-color: rgba(105, 217, 226, .25); } .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17424"] .mptt-event-container, .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17425"] .mptt-event-container{ background-color: rgba(226, 152, 178, 0.15); } .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17424"] .mptt-event-container:hover, .mptt-shortcode-wrapper .mptt-shortcode-event.mptt-event-vertical-top[data-column-id="17425"] .mptt-event-container:hover{ background-color: rgba(226, 152, 178, .25); } .mptt-shortcode-list { color: white; } [data-event-id="17452"] .timeslot{ display: none; } .mptt-shortcode-wrapper .mptt-shortcode-table tbody .mptt-event-container[data-event-id="17452"] .event-subtitle { font-size: .9em; } .mfp-content { position: relative; background-color: #FFF; padding: 40px 20px; width: 90%; max-width: 700px; margin: 20px auto; } .mfp-content h4{ text-align: center; } .mfp-content .timeslots-title,.mfp-content .timeslot{ display: none; } .mfp-preloader{ color: black; } .mfp-content{ position: relative; background-color: #FFF!important; padding: 40px 20px; width: 90%; max-width: 700px; margin: 20px auto;} .mptt-event-container.id-56 a{ font-weight:bold; color: rgb(0, 188, 221)!important; } .mptt-event-container.id-56 a::before{ } .mptt-event-container.id-63,.mptt-event-container.id-64 { background-image: url(https://staging6.odsc.com/wp-content/uploads/2018/05/DinnerDS.jpg);} .mptt-event-container.id-121,.mptt-event-container.id-64 { background-image: url(https://staging6.odsc.com/wp-content/uploads/2017/09/Data-Robot-Networking-Party1.jpg);} .linkic{width: 100%; height: 100%; position: absolute;} .overl{ position: absolute; top: 35%; background: url(https://staging6.odsc.com/wp-content/uploads/2018/05/play-white.svg); width: 20%; background-repeat: no-repeat; left: 40%; height: 100%;} #hu-header-mobile .hu-header-logo { max-height: 75px; margin: 41px auto 0; display: none!important; } .agendica tbody tr:nth-child(2n+2) { background-color: transparent!important; } .agendica tr.mptt-shortcode-row th { background-color: transparent!important; } .agendica tbody td.event { background-color: transparent!important; } .agendica .mptt-shortcode-hours{color:white!important} .agendica th{color:white!important} .agendica .timeslot{color:white!important} .agendica .event-subtitle{color:white!important} .agendica .event-title{color:white!important} .price__table__column .column__header { height: 250px!important; } .price__table__column .column__header .column__desc { font-size: 15px!important; line-height: 20px!important; } .faq_categories .attending { background: url(images/attendee.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .attending.activated { background: url(images/attendee_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .hiring { background: url(images/hiring.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .hiring.activated { background: url(images/hiring_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .videos { background: url(images/videos.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .videos.activated { background: url(images/videos_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .speakers { background: url(images/speaker.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .speakers.activated { background: url(images/speaker_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .volunteers { background: url(images/volunteer.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .volunteers.activated { background: url(images/volunteer_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .sponsor { background: url(images/sponsor.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .sponsor.activated { background: url(images/sponsor_light.svg) no-repeat center 15px #fff; background-size: 37px; } .faq_categories .group-tickets { background: url(images/group.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .ticket-type { background: url(images/ticket.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .schedule, .faq_categories .odsc { background: url(images/schedule.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .refund-policy { background: url(images/refund.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .trainings { background: url(images/training.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .app-info { background: url(images/mobile.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .scholarships { background: url(images/scholarship.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .promotions-pricing { background: url(images/pricing.svg) no-repeat center 12px #fff; background-size: 27px; } .faq_categories .odsc-europe-2017, .faq_categories .odsc-west-2017, .faq_categories .odsc-east-2017 { background: url(images/logo.png) no-repeat center 10px #fff; background-size: 37px; padding-top: 35px; } .faq_categories li a { font-size: 15px; line-height: 20px; display: inline-block; width: 120px; height: 60px; padding-top: 60px; border-radius: 50%; -moz-border-radius: 50%; -webkit-border-radius: 50%; text-align: center; /* padding: 10px 15px 10px 50px; */ background: #fff; -webkit-box-shadow: 0px 3px 3px rgba(0,0,0,0.25); -moz-box-shadow: 0px 3px 3px rgba(0,0,0,0.25); box-shadow: 0px 3px 3px rgba(0,0,0,0.25); } @media only screen and (min-width: 992px){ .tcode-event-schedule .col-md-2 { width: 8.33333333%; } .tcode-event-schedule .col-md-9 { width: 83.33333333%; } .tcode-event-schedule .col-md-8{ width: 83.33333333%; } .tcode-event-schedule .col-md-offset-2 { margin-left: 8.33333333%; } } </style>   <script class="hsq-set-content-id" data-content-id="blog-post"> var _hsq = _hsq || []; _hsq.push(["setContentType", "blog-post"]); </script>  <noscript><style type="text/css">.mptt-shortcode-wrapper .mptt-shortcode-table:first-of-type{display:table!important}.mptt-shortcode-wrapper .mptt-shortcode-table .mptt-event-container:hover{height:auto!important;min-height:100%!important}body.mprm_ie .mptt-shortcode-wrapper .mptt-event-container{height:auto!important}@media (max-width:767px){.mptt-shortcode-wrapper .mptt-shortcode-table:first-of-type{display:none!important}}</style></noscript><meta name="facebook-domain-verification" content="am2vglo5kisnxesykxjg911bcapxcr" /> <script type="text/javascript"> var ajaxurl = 'https://odsc.com/wp-admin/admin-ajax.php'; </script> <script type='text/javascript'> var video_popup_unprm_general_settings = { 'unprm_r_border': '' }; </script> <style type="text/css" media="all" id="wcs_styles"></style><noscript><style>.wp-grid-builder .wpgb-card.wpgb-card-hidden .wpgb-card-wrapper{opacity:1!important;visibility:visible!important;transform:none!important}.wpgb-facet {opacity:1!important;pointer-events:auto!important}.wpgb-facet *:not(.wpgb-pagination-facet){display:none}</style></noscript>   <script data-cfasync="false" data-pagespeed-no-defer> var dataLayer_content = {"pagePostType":"etn-speaker","pagePostType2":"single-etn-speaker","pagePostAuthor":"Jay H"}; dataLayer.push( dataLayer_content ); </script> <script data-cfasync="false"> (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= '//www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-M62L34N'); </script> <style id = "be-dynamic-css" type="text/css"> body { background-color: rgb(255,255,255);background-color: rgba(255,255,255,1);} .layout-box #header-inner-wrap, #header-inner-wrap, body.header-transparent #header #header-inner-wrap.no-transparent, .left-header .sb-slidebar.sb-left, .left-header .sb-slidebar.sb-left #slidebar-menu a::before { background-color: rgb(50,56,64);background-color: rgba(50,56,64,1);} #mobile-menu, #mobile-menu ul { background-color: rgb(50,56,64);background-color: rgba(50,56,64,1);} #mobile-menu li{ border-bottom-color: #efefef ; } body.header-transparent #header-inner-wrap{ background: transparent; } .be-gdpr-modal-item input:checked + .slider{ background-color: #00bcdd; } .be-gdpr-modal-iteminput:focus + .slider { box-shadow: 0 0 1px #00bcdd; } .be-gdpr-modal-item .slider:before { background-color:#ffffff; } .be-gdpr-cookie-notice-bar .be-gdpr-cookie-notice-button{ background: #00bcdd; color: #ffffff; } #header .header-border{ border-bottom: 0px none #00bcdd; } #header-top-bar{ background-color: rgb(21,22,26);background-color: rgba(21,22,26,1); border-bottom: 0px none #ffffff; color: #ffffff; } #header-top-bar #topbar-menu li a{ color: #ffffff; } #header-bottom-bar{ background-color: rgb(255,255,255);background-color: rgba(255,255,255,1); border-top: none #323232; border-bottom: none #323232; } /*Adjusted the timings for the new effects*/ body.header-transparent #header #header-inner-wrap { -webkit-transition: background .25s ease, box-shadow .25s ease, opacity 700ms cubic-bezier(0.645, 0.045, 0.355, 1), transform 700ms cubic-bezier(0.645, 0.045, 0.355, 1); -moz-transition: background .25s ease, box-shadow .25s ease, opacity 700ms cubic-bezier(0.645, 0.045, 0.355, 1), transform 700ms cubic-bezier(0.645, 0.045, 0.355, 1); 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} .layout-box-top, .layout-box-bottom, .layout-box-right, .layout-box-left, .layout-border-header-top #header-inner-wrap, .layout-border-header-top.layout-box #header-inner-wrap, body.header-transparent .layout-border-header-top #header #header-inner-wrap.no-transparent { background-color: rgb(211,211,211);background-color: rgba(211,211,211,1);} .left-header.left-sliding.left-overlay-menu .sb-slidebar{ background-color: rgb(8,8,8);background-color: rgba(8,8,8,0.90); } .top-header.top-overlay-menu .sb-slidebar{ background-color: rgb(26,26,26);background-color: rgba(26,26,26,1);} .search-box-wrapper{ background-color: rgb(255,255,255);background-color: rgba(255,255,255,0.85);} .search-box-wrapper.style1-header-search-widget input[type="text"]{ background-color: transparent !important; color: #000000; border: 1px solid #000000; } .search-box-wrapper.style2-header-search-widget input[type="text"]{ background-color: transparent !important; color: #000000; border: none !important; box-shadow: none !important; } .search-box-wrapper .searchform .search-icon{ color: #000000; } #header-top-bar-right .search-box-wrapper.style1-header-search-widget input[type="text"]{ border: none; } .post-title , .post-date-wrap { margin-bottom: 12px; } /* ====================== Dynamic Border Styling ====================== */ .layout-box-top, .layout-box-bottom { height: 30px; } .layout-box-right, .layout-box-left { width: 30px; } #main.layout-border, #main.layout-border.layout-border-header-top{ padding: 30px; } .left-header #main.layout-border { padding-left: 0px; } #main.layout-border.layout-border-header-top { padding-top: 0px; } .be-themes-layout-layout-border #logo-sidebar, .be-themes-layout-layout-border-header-top #logo-sidebar{ margin-top: 70px; } /*Left Static Menu*/ .left-header.left-static.be-themes-layout-layout-border #main-wrapper{ margin-left: 310px; } .left-header.left-static.be-themes-layout-layout-border .sb-slidebar.sb-left { left: 30px; } /*Right Slidebar*/ body.be-themes-layout-layout-border-header-top .sb-slidebar.sb-right, body.be-themes-layout-layout-border .sb-slidebar.sb-right { right: -250px; } .be-themes-layout-layout-border-header-top .sb-slidebar.sb-right.opened, .be-themes-layout-layout-border .sb-slidebar.sb-right.opened { right: 30px; } /* Top-overlay menu on opening, header moves sideways bug. Fixed on the next line code */ /*body.be-themes-layout-layout-border-header-top.top-header.slider-bar-opened #main #header #header-inner-wrap.no-transparent.top-animate, body.be-themes-layout-layout-border.top-header.slider-bar-opened #main #header #header-inner-wrap.no-transparent.top-animate { right: 310px; }*/ body.be-themes-layout-layout-border-header-top.top-header:not(.top-overlay-menu).slider-bar-opened #main #header #header-inner-wrap.no-transparent.top-animate, body.be-themes-layout-layout-border.top-header:not(.top-overlay-menu).slider-bar-opened #main #header #header-inner-wrap.no-transparent.top-animate { right: 310px; } /* Now not needed mostly, as the hero section image is coming properly */ /*Single Page Version*/ body.be-themes-layout-layout-border-header-top.single-page-version .single-page-nav-wrap, body.be-themes-layout-layout-border.single-page-version .single-page-nav-wrap { right: 50px; } /*Split Screen Page Template*/ .top-header .layout-border #content.page-split-screen-left { margin-left: calc(50% + 15px); } .top-header.page-template-page-splitscreen-left .layout-border .header-hero-section { width: calc(50% - 15px); } .top-header .layout-border #content.page-split-screen-right { width: calc(50% - 15px); } .top-header.page-template-page-splitscreen-right .layout-border .header-hero-section { left: calc(50% - 15px); } @media only screen and (max-width: 960px) { body.be-themes-layout-layout-border-header-top.single-page-version .single-page-nav-wrap, body.be-themes-layout-layout-border.single-page-version .single-page-nav-wrap { right: 35px; } body.be-themes-layout-layout-border-header-top .sb-slidebar.sb-right, body.be-themes-layout-layout-border .sb-slidebar.sb-right { right: -280px; } #main.layout-border, #main.layout-border.layout-border-header-top { padding: 0px !important; } .top-header .layout-border #content.page-split-screen-left, .top-header .layout-border #content.page-split-screen-right { margin-left: 0px; width:100%; } .top-header.page-template-page-splitscreen-right .layout-border .header-hero-section, .top-header.page-template-page-splitscreen-left .layout-border .header-hero-section { width:100%; } } body, .special-heading-wrap .caption-wrap .body-font, .woocommerce .woocommerce-ordering select.orderby, .woocommerce-page .woocommerce-ordering select.orderby { font: 400 18px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #5f6263; line-height: 26px; letter-spacing: 0px; text-transform: none; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } h1 { font: 700 55px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 70px; letter-spacing: 0px; text-transform: none;} h2 { font: 700 42px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 63px; letter-spacing: 0px; text-transform: none;} h3 { font: 700 35px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 52px; letter-spacing: 1px; text-transform: none;} h4, .woocommerce-order-received .woocommerce h2, .woocommerce-order-received .woocommerce h3, .woocommerce-view-order .woocommerce h2, .woocommerce-view-order .woocommerce h3{ font: 400 26px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 42px; letter-spacing: 0px; text-transform: none;} h5, #reply-title { font: 400 20px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 36px; letter-spacing: 0px; text-transform: none; } h6, .testimonial-author-role.h6-font, .menu-card-title, .menu-card-item-price, .slider-counts, .woocommerce-MyAccount-navigation ul li { font: 400 15px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 32px; letter-spacing: 0px; text-transform: none;} h6.gallery-side-heading { font-size: 18px; } .special-subtitle , .style1.thumb-title-wrap .portfolio-item-cats { font-style: ; font-size: 15px; font-weight: ; font-family: Crimson Text; text-transform: none; letter-spacing: 0px; } .gallery-side-heading { font-size: 18px; } .attachment-details-custom-slider { background-color: rgb(0,0,0);background-color: rgba(0,0,0,1); font: 15px "Crimson Text","Open Sans","Arial",sans-serif; color: ; line-height: 15px; letter-spacing: 0px; text-transform: none;} .single-portfolio-slider .carousel_bar_wrap { background-color: rgb(255,255,255);background-color: rgba(255,255,255,0.5);} .top-right-sliding-menu .sb-right ul#slidebar-menu li, .overlay-menu-close, .be-overlay-menu-close { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 50px; letter-spacing: 1px; text-transform: uppercase;} .top-right-sliding-menu .sb-right ul#slidebar-menu li a { color: #ffffff !important; } .top-right-sliding-menu .sb-right #slidebar-menu ul.sub-menu li { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 25px; letter-spacing: ; text-transform: none;} .top-right-sliding-menu .sb-right ul#slidebar-menu li a { color: #ffffff !important; } .sb-right #slidebar-menu .mega .sub-menu .highlight .sf-with-ul { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 50px; letter-spacing: 1px; text-transform: uppercase; color: #ffffff !important; } .post-meta.post-top-meta-typo, .style8-blog .post-meta.post-category a, .hero-section-blog-categories-wrap a { font: 12px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #757575; line-height: 24px; letter-spacing: 0px; text-transform: uppercase;; } #portfolio-title-nav-bottom-wrap h6, #portfolio-title-nav-bottom-wrap .slider-counts { font: 400 15px "Montserrat","Open Sans","Arial",sans-serif; color: ; line-height: ; letter-spacing: 0px; text-transform: none;; line-height: 40px; } .filters .filter_item { font: 400 12px "Montserrat","Open Sans","Arial",sans-serif; color: #222222; line-height: 32px; letter-spacing: 1px; text-transform: uppercase;; } ul#mobile-menu a { font: 400 12px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 40px; letter-spacing: 1px; text-transform: uppercase;} ul#mobile-menu ul.sub-menu a { font: 400 13px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #bbbbbb; line-height: 27px; letter-spacing: 0px; text-transform: none; } ul#mobile-menu li.mega ul.sub-menu li.highlight > :first-child { font: 400 12px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 40px; letter-spacing: 1px; text-transform: uppercase;} #navigation, .style2 #navigation, .style13 #navigation, #navigation-left-side, #navigation-right-side, .sb-left #slidebar-menu, .header-widgets, .header-code-widgets, body #header-inner-wrap.top-animate.style2 #navigation, .top-overlay-menu .sb-right #slidebar-menu, #navigation .mega .sub-menu .highlight .sf-with-ul, .special-header-menu .menu-container { font: 600 16px "Montserrat","Open Sans","Arial",sans-serif; color: #00bcdd; line-height: 51px; letter-spacing: 1px; text-transform: uppercase;} #navigation .sub-menu, #navigation .children, #navigation-left-side .sub-menu, #navigation-left-side .children, #navigation-right-side .sub-menu, #navigation-right-side .children, .sb-left #slidebar-menu .sub-menu, .top-overlay-menu .sb-right #slidebar-menu .sub-menu, .special-header-menu .menu-container .sub-menu, .special-header-menu .sub-menu { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #bbbbbb; line-height: 28px; letter-spacing: 0px; text-transform: none;} .thumb-title-wrap .thumb-title { font: 400 14px "Montserrat","Open Sans","Arial",sans-serif; color: ; line-height: 30px; letter-spacing: 0px; text-transform: uppercase;} .thumb-title-wrap .portfolio-item-cats { font-size: 12px; line-height: 17px; text-transform: none; letter-spacing: 0px; } .full-screen-portfolio-overlay-title { font: 400 14px "Montserrat","Open Sans","Arial",sans-serif; color: ; line-height: 30px; letter-spacing: 0px; text-transform: uppercase;} #footer { font: 400 14px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 14px; letter-spacing: 0px; text-transform: none;} #bottom-widgets h6 { font: 400 18px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #474747; line-height: 22px; letter-spacing: 1px; text-transform: uppercase; margin-bottom:20px; } #bottom-widgets { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #757575; line-height: 24px; letter-spacing: 0px; text-transform: none;} .sidebar-widgets h6 { font: 400 18px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #333333; line-height: 22px; letter-spacing: 1px; text-transform: uppercase; margin-bottom:20px; } .sidebar-widgets { ?php be_themes_print_typography('sidebar_widget_text'); ?> } .sb-slidebar .widget { font: 400 14px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #a2a2a2; line-height: 25px; letter-spacing: 0px; text-transform: none;} .sb-slidebar .widget h6 { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #ffffff; line-height: 22px; letter-spacing: 1px; text-transform: none;} .woocommerce ul.products li.product .product-meta-data h3, .woocommerce-page ul.products li.product .product-meta-data h3, .woocommerce ul.products li.product h3, .woocommerce-page ul.products li.product h3 { font: 400 13px "Montserrat","Open Sans","Arial",sans-serif; color: #222222; line-height: 27px; letter-spacing: 1px; text-transform: uppercase;} .woocommerce ul.products li.product .product-meta-data .woocommerce-loop-product__title, .woocommerce-page ul.products li.product .product-meta-data .woocommerce-loop-product__title, .woocommerce ul.products li.product .woocommerce-loop-product__title, .woocommerce-page ul.products li.product .woocommerce-loop-product__title, .woocommerce ul.products li.product-category .woocommerce-loop-category__title, .woocommerce-page ul.products li.product-category .woocommerce-loop-category__title { font: 400 13px "Montserrat","Open Sans","Arial",sans-serif; color: #222222; line-height: 27px; letter-spacing: 1px; text-transform: uppercase; margin-bottom:5px; text-align: center; } .woocommerce-page.single.single-product #content div.product h1.product_title.entry-title { font: 400 25px "Montserrat","Open Sans","Arial",sans-serif; color: #222222; line-height: 27px; letter-spacing: 0px; text-transform: none;} .contact_form_module input[type="text"], .contact_form_module textarea { font: 400 13px "Montserrat","Open Sans","Arial",sans-serif; color: #222222; line-height: 26px; letter-spacing: 0px; text-transform: none;} .page-title-module-custom .page-title-custom, h6.portfolio-title-nav{ font: 400 18px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 36px; letter-spacing: 3px; text-transform: uppercase;} .tatsu-button, .be-button, .woocommerce a.button, .woocommerce-page a.button, .woocommerce button.button, .woocommerce-page button.button, .woocommerce input.button, .woocommerce-page input.button, .woocommerce #respond input#submit, .woocommerce-page #respond input#submit, .woocommerce #content input.button, .woocommerce-page #content input.button, input[type="submit"], .more-link.style1-button, .more-link.style2-button, .more-link.style3-button, input[type="button"], input[type="submit"], input[type="reset"], button, input[type="file"]::-webkit-file-upload-button { font-family: Source Sans Pro; font-weight: ; } .post-title , .post-date-wrap { font: 400 20px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #000000; line-height: 40px; letter-spacing: 0px; text-transform: none; margin-bottom: 12px; } .style3-blog .post-title, .style8-blog .post-title { font: 400 16px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #363c3b; line-height: 28px; letter-spacing: 0px; text-transform: none;} .post-nav li, .style8-blog .post-meta.post-date, .style8-blog .post-bottom-meta-wrap, .hero-section-blog-bottom-meta-wrap { font: 12px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #757575; line-height: 24px; letter-spacing: 0px; text-transform: uppercase;} .ui-tabs-anchor, .accordion .accordion-head, .skill-wrap .skill_name, .chart-wrap span, .animate-number-wrap h6 span, .woocommerce-tabs .tabs li a, .be-countdown { font-family: Source Sans Pro; letter-spacing: 0px; font-style: ; font-weight: 600; } .ui-tabs-anchor { font-size: 13px; line-height: 17px; text-transform: uppercase; } .accordion .accordion-head { font-size: 18px; line-height: 17px; text-transform: uppercase; } .skill-wrap .skill_name { font-size: 20px; line-height: 17px; text-transform: none; } .countdown-section { font-size: 15px; line-height: 30px; text-transform: uppercase; } .countdown-amount { font-size: 55px; line-height: 95px; text-transform: uppercase; } .tweet-slides .tweet-content { font-family: Source Sans Pro; letter-spacing: 0px; font-style: ; font-weight: ; text-transform: none; } .testimonial_slide .testimonial-content { font-family: Crimson Text; letter-spacing: 0px; font-style: ; font-weight: ; text-transform: none; } .oshine-animated-link, .view-project-link.style4-button { font-family: Montserrat; font-weight: ; letter-spacing: ; font-style: ; text-transform: none; } a.navigation-previous-post-link, a.navigation-next-post-link { font: 700 13px "Montserrat","Open Sans","Arial",sans-serif; color: ; line-height: 20px; letter-spacing: 0px; text-transform: none;; } @media only screen and (max-width : 767px ) { #hero-section h1 , .full-screen-section-wrap h1, .tatsu-fullscreen-wrap h1 { font-size: 30px; line-height: 40px; } #hero-section h2, .full-screen-section-wrap h2, .tatsu-fullscreen-wrap h2 { font-size: 25px; line-height: 35px; } #hero-section h4, .full-screen-section-wrap h4, .tatsu-fullscreen-wrap h3 { font-size: 16px; line-height: 30px; } #hero-section h5, .full-screen-section-wrap h5, .tatsu-fullscreen-wrap h5 { font-size: 16px; line-height: 30px; } } /* RELATED TO TYPOGRAPHY */ #header-controls-right, #header-controls-left { color: #00bcdd} #be-left-strip .be-mobile-menu-icon span { background-color: #323232} ul#mobile-menu .mobile-sub-menu-controller { line-height : 40px ; } ul#mobile-menu ul.sub-menu .mobile-sub-menu-controller{ line-height : 27px ; } .breadcrumbs { color: #515151; } .search-box-wrapper.style2-header-search-widget input[type="text"]{ font-style: ; font-weight: ; font-family: Crimson Text; } .portfolio-share a.custom-share-button, .portfolio-share a.custom-share-button:active, .portfolio-share a.custom-share-button:hover, .portfolio-share a.custom-share-button:visited { color: #515151; } .more-link.style2-button { color: #000000 !important; border-color: #000000 !important; } .style8-blog .post-bottom-meta-wrap .be-share-stack a.custom-share-button, .style8-blog .post-bottom-meta-wrap .be-share-stack a.custom-share-button:active, .style8-blog .post-bottom-meta-wrap .be-share-stack a.custom-share-button:hover, .style8-blog .post-bottom-meta-wrap .be-share-stack a.custom-share-button:visited { color: #757575; } .hero-section-blog-categories-wrap a, .hero-section-blog-categories-wrap a:visited, .hero-section-blog-categories-wrap a:hover, .hero-section-blog-bottom-meta-wrap .hero-section-blog-bottom-meta-wrap a, .hero-section-blog-bottom-meta-wrap a:visited, .hero-section-blog-bottom-meta-wrap a:hover { color : #000000; } #navigation .mega .sub-menu .highlight .sf-with-ul { color: #bbbbbb !important; line-height:1.5; } .view-project-link.style4-button { color : #515151; } .pricing-table .pricing-feature{ font-size: 17px; } /* Woocommerce */ .related.products h2, .upsells.products h2, .cart-collaterals .cross-sells h2, .cart_totals h2, .shipping_calculator h2, .woocommerce-billing-fields h3, .woocommerce-shipping-fields h3, .shipping_calculator h2, #order_review_heading, .woocommerce .page-title { font-family: Montserrat; font-weight: 400; } .woocommerce form .form-row label, .woocommerce-page form .form-row label { color: #515151; } .woocommerce-tabs .tabs li a { color: #515151 !important; } /* BB Press Plugin */ a.bbp-forum-title, #bbpress-forums fieldset.bbp-form label, .bbp-topic-title a.bbp-topic-permalink { font: 400 15px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 32px; letter-spacing: 0px; text-transform: none;} #bbpress-forums ul.forum-titles li, #bbpress-forums ul.bbp-replies li.bbp-header { font: 400 15px "Source Sans Pro","Open Sans","Arial",sans-serif; color: #515151; line-height: 32px; letter-spacing: 0px; text-transform: none; line-height: inherit; letter-spacing: inherit; text-transform: uppercase; font-size: inherit; } #bbpress-forums .topic .bbp-topic-meta a, .bbp-forum-freshness a, .bbp-topic-freshness a, .bbp-header .bbp-reply-content a, .bbp-topic-tags a, .bbp-breadcrumb a, .bbp-forums-list a { color: #515151; } /*Event On Plugin*/ .ajde_evcal_calendar .calendar_header p, .eventon_events_list .eventon_list_event .evcal_cblock { font-family: Source Sans Pro !important; } .eventon_events_list .eventon_list_event .evcal_desc span.evcal_desc2, .evo_pop_body .evcal_desc span.evcal_desc2 { font-family: Source Sans Pro !important; font-size: 14px !important; text-transform: none; } .eventon_events_list .eventon_list_event .evcal_desc span.evcal_event_subtitle, .evo_pop_body .evcal_desc span.evcal_event_subtitle, .evcal_evdata_row .evcal_evdata_cell p, #evcal_list .eventon_list_event p.no_events { text-transform: none !important; font-family: Source Sans Pro !important; font-size: inherit !important; } /* END RELATED TO TYPOGRAPHY */ .filters.single_border .filter_item{ border-color: #00bcdd; } .filters.rounded .current_choice{ border-radius: 50px; background-color: #00bcdd; color: #ffffff; } .filters.single_border .current_choice, .filters.border .current_choice{ color: #00bcdd; } .exclusive-mobile-bg .menu-controls{ background-color: background-color: rgb(255,255,255);background-color: rgba(255,255,255,0);; } #header .be-mobile-menu-icon span { background-color : #323232; } #header-controls-right, #header-controls-left, .overlay-menu-close, .be-overlay-menu-close { color : #323232; } #header .exclusive-mobile-bg .be-mobile-menu-icon, #header .exclusive-mobile-bg .be-mobile-menu-icon span, #header-inner-wrap.background--light.transparent.exclusive-mobile-bg .be-mobile-menu-icon, #header-inner-wrap.background--light.transparent.exclusive-mobile-bg .be-mobile-menu-icon span, #header-inner-wrap.background--dark.transparent.exclusive-mobile-bg .be-mobile-menu-icon, #header-inner-wrap.background--dark.transparent.exclusive-mobile-bg .be-mobile-menu-icon span { background-color: #323232} .be-mobile-menu-icon{ width: 18px; height: 2px; } .be-mobile-menu-icon .hamburger-line-1{ top: -5px; } .be-mobile-menu-icon .hamburger-line-3{ top: 5px; } .thumb-title-wrap { color: #ffffff; } #bottom-widgets .widget ul li a, #bottom-widgets a { color: inherit; } #bottom-widgets .tagcloud a:hover { color: #ffffff; } a, a:visited, a:hover, #bottom-widgets .widget ul li a:hover, #bottom-widgets a:hover{ color: #00bcdd; } #header-top-menu a:hover, #navigation .current_page_item a, #navigation .current_page_item a:hover, #navigation a:hover, #navigation-left-side .current_page_item a, #navigation-left-side .current_page_item a:hover, #navigation-left-side a:hover, #navigation-right-side .current_page_item a, #navigation-right-side .current_page_item a:hover, #navigation-right-side a:hover, #menu li.current-menu-ancestor > a, #navigation .current-menu-item > a, #navigation .sub-menu .current-menu-item > a, #navigation .sub-menu a:hover, #navigation .children .current-menu-item > a, #navigation .children a:hover, #slidebar-menu .current-menu-item > a, .special-header-menu a:hover + .mobile-sub-menu-controller i, .special-header-menu #slidebar-menu a:hover, .special-header-menu .sub-menu a:hover, .single-page-version #navigation a:hover, .single-page-version #navigation-left-side a:hover, .single-page-version #navigation-right-side a:hover, .single-page-version #navigation .current-section.current_page_item a, .single-page-version #navigation-left-side .current-section.current_page_item a, .single-page-version #navigation-right-side .current-section.current_page_item a, .single-page-version #slidebar-menu .current-section.current_page_item a, .single-page-version #navigation .current_page_item a:hover, .single-page-version #navigation-left-side .current_page_item a:hover, .single-page-version #navigation-right-side .current_page_item a:hover, .single-page-version #slidebar-menu .current_page_item a:hover, .be-sticky-sections #navigation a:hover, .be-sticky-sections #navigation-left-side a:hover, .be-sticky-sections #navigation-right-side a:hover, .be-sticky-sections #navigation .current-section.current_page_item a, .be-sticky-sections #navigation-left-side .current-section.current_page_item a, .be-sticky-sections #navigation-right-side .current-section.current_page_item a, .be-sticky-sections #navigation .current_page_item a:hover, .be-sticky-sections #navigation-left-side .current_page_item a:hover, .be-sticky-sections #navigation-right-side .current_page_item a:hover, #navigation .current-menu-ancestor > a, #navigation-left-side .current-menu-ancestor > a, #navigation-right-side .current-menu-ancestor > a, #slidebar-menu .current-menu-ancestor > a, .special-header-menu .current-menu-item > a, .sb-left #slidebar-menu a:hover { color: #ffffff; } #navigation .current_page_item ul li a, #navigation-left-side .current_page_item ul li a, #navigation-right-side .current_page_item ul li a, .single-page-version #navigation .current_page_item a, .single-page-version #navigation-left-side .current_page_item a, .single-page-version #navigation-right-side .current_page_item a, .single-page-version #slidebar-menu .current_page_item a, .single-page-version #navigation .sub-menu .current-menu-item > a, .single-page-version #navigation .children .current-menu-item > a .be-sticky-sections #navigation .current_page_item a, .be-sticky-sections #navigation-left-side .current_page_item a, .be-sticky-sections #navigation-right-side .current_page_item a, .be-sticky-sections #navigation .sub-menu .current-menu-item > a, .be-sticky-sections #navigation .children .current-menu-item > a { color: inherit; } .be-nav-link-effect-1 a::after, .be-nav-link-effect-2 a::after, .be-nav-link-effect-3 a::after{ background-color: rgb(255,255,255);background-color: rgba(255,255,255,1);} #portfolio-title-nav-wrap .portfolio-nav a { color: #00bcdd; } #portfolio-title-nav-wrap .portfolio-nav a .home-grid-icon span{ background-color: #00bcdd; } #portfolio-title-nav-wrap .portfolio-nav a:hover { color: #323840; } #portfolio-title-nav-wrap .portfolio-nav a:hover .home-grid-icon span{ background-color: #323840; } .page-title-module-custom .header-breadcrumb { line-height: 36px; } #portfolio-title-nav-bottom-wrap h6, #portfolio-title-nav-bottom-wrap ul li a, .single_portfolio_info_close, #portfolio-title-nav-bottom-wrap .slider-counts{ background-color: rgb(255,255,255);background-color: rgba(255,255,255,0);} .more-link.style2-button:hover { border-color: #00bcdd !important; background: #00bcdd !important; color: #ffffff !important; } .woocommerce a.button, .woocommerce-page a.button, .woocommerce button.button, .woocommerce-page button.button, .woocommerce input.button, .woocommerce-page input.button, .woocommerce #respond input#submit, .woocommerce-page #respond input#submit, .woocommerce #content input.button, .woocommerce-page #content input.button { background: transparent !important; color: #000 !important; border-color: #000 !important; border-style: solid !important; border-width: 2px !important; background: transparent !important; color: #000000 !important; border-width: 2px !important; border-color: #000000 !important; line-height: 41px; text-transform: uppercase; } .woocommerce a.button:hover, .woocommerce-page a.button:hover, .woocommerce button.button:hover, .woocommerce-page button.button:hover, .woocommerce input.button:hover, .woocommerce-page input.button:hover, .woocommerce #respond input#submit:hover, .woocommerce-page #respond input#submit:hover, .woocommerce #content input.button:hover, .woocommerce-page #content input.button:hover { background: #e0a240 !important; color: #fff !important; border-color: #e0a240 !important; border-width: 2px !important; background: #e0a240 !important; color: #ffffff !important; border-color: #e0a240 !important; } .woocommerce a.button.alt, .woocommerce-page a.button.alt, .woocommerce .button.alt, .woocommerce-page .button.alt, .woocommerce input.button.alt, .woocommerce-page input.button.alt, .woocommerce input[type="submit"].alt, .woocommerce-page input[type="submit"].alt, .woocommerce #respond input#submit.alt, .woocommerce-page #respond input#submit.alt, .woocommerce #content input.button.alt, .woocommerce-page #content input.button.alt { background: #e0a240 !important; color: #fff !important; border-color: #e0a240 !important; border-style: solid !important; border-width: 2px !important; background: #e0a240 !important; color: #ffffff !important; border-width: 2px !important; border-color: #e0a240 !important; line-height: 41px; text-transform: uppercase; } .woocommerce a.button.alt:hover, .woocommerce-page a.button.alt:hover, .woocommerce .button.alt:hover, .woocommerce-page .button.alt:hover, .woocommerce input[type="submit"].alt:hover, .woocommerce-page input[type="submit"].alt:hover, .woocommerce input.button.alt:hover, .woocommerce-page input.button.alt:hover, .woocommerce #respond input#submit.alt:hover, .woocommerce-page #respond input#submit.alt:hover, .woocommerce #content input.button.alt:hover, .woocommerce-page #content input.button.alt:hover { background: transparent !important; color: #000 !important; border-color: #000 !important; border-style: solid !important; border-width: 2px !important; background: transparent !important; color: #000000 !important; border-color: #000000 !important; } .woocommerce .woocommerce-message a.button, .woocommerce-page .woocommerce-message a.button, .woocommerce .woocommerce-message a.button:hover, .woocommerce-page .woocommerce-message a.button:hover { border: none !important; color: #fff !important; background: none !important; } .woocommerce .woocommerce-ordering select.orderby, .woocommerce-page .woocommerce-ordering select.orderby { border-color: #eeeeee; } .style7-blog .post-title{ margin-bottom: 9px; } .style8-blog .post-comment-wrap a:hover{ color : #00bcdd; } .style8-blog .element:not(.be-image-post) .post-details-wrap{ background-color: #ffffff ; } .accordion .accordion-head.with-bg.ui-accordion-header-active{ background-color: #00bcdd; color: #ffffff !important; } #portfolio-title-nav-wrap{ padding-top: 15px; padding-bottom: 15px; border-bottom: 1px solid #cecece; } #portfolio-title-nav-bottom-wrap h6, #portfolio-title-nav-bottom-wrap ul, .single_portfolio_info_close .font-icon, .slider-counts{ color: #2b2b2b ; } #portfolio-title-nav-bottom-wrap .home-grid-icon span{ background-color: #2b2b2b ; } #portfolio-title-nav-bottom-wrap h6:hover, #portfolio-title-nav-bottom-wrap ul a:hover, #portfolio-title-nav-bottom-wrap .slider-counts:hover, .single_portfolio_info_close:hover { background-color: rgb(235,73,73);background-color: rgba(235,73,73,0.85);} #portfolio-title-nav-bottom-wrap h6:hover, #portfolio-title-nav-bottom-wrap ul a:hover, #portfolio-title-nav-bottom-wrap .slider-counts:hover, .single_portfolio_info_close:hover .font-icon{ color: #ffffff ; } #portfolio-title-nav-bottom-wrap ul a:hover .home-grid-icon span{ background-color: #ffffff ; } /* ====================== Layout ====================== */ body #header-inner-wrap.top-animate #navigation, body #header-inner-wrap.top-animate .header-controls, body #header-inner-wrap.stuck #navigation, body #header-inner-wrap.stuck .header-controls { -webkit-transition: line-height 0.5s ease; -moz-transition: line-height 0.5s ease; -ms-transition: line-height 0.5s ease; -o-transition: line-height 0.5s ease; transition: line-height 0.5s ease; } .header-cart-controls .cart-contents span{ background: #646464; } .header-cart-controls .cart-contents span{ color: #f5f5f5; } .left-sidebar-page, .right-sidebar-page, .no-sidebar-page .be-section-pad:first-child, .page-template-page-940-php #content , .no-sidebar-page #content-wrap, .portfolio-archives.no-sidebar-page #content-wrap { padding-top: 80px; padding-bottom: 80px; } .no-sidebar-page #content-wrap.page-builder{ padding-top: 0px; padding-bottom: 0px; } .left-sidebar-page .be-section:first-child, .right-sidebar-page .be-section:first-child, .dual-sidebar-page .be-section:first-child { padding-top: 0 !important; } .style1 .logo, .style4 .logo, #left-header-mobile .logo, .style3 .logo, .style7 .logo, .style10 .logo{ padding-top: 15px; padding-bottom: 15px; } .style5 .logo, .style6 .logo{ margin-top: 15px; margin-bottom: 15px; } #footer-wrap { padding-top: 25px; padding-bottom: 25px; } /* ====================== Colors ====================== */ .sec-bg, .gallery_content, .fixed-sidebar-page .fixed-sidebar, .style3-blog .blog-post.element .element-inner, .style4-blog .blog-post, .blog-post.format-link .element-inner, .blog-post.format-quote .element-inner, .woocommerce ul.products li.product, .woocommerce-page ul.products li.product, .chosen-container.chosen-container-single .chosen-drop, .chosen-container.chosen-container-single .chosen-single, .chosen-container.chosen-container-active.chosen-with-drop .chosen-single { background: #fafbfd; } .sec-color, .post-meta a, .pagination a, .pagination a:visited, .pagination span, .pages_list a, input[type="text"], input[type="email"], input[type="password"], textarea, .gallery_content, .fixed-sidebar-page .fixed-sidebar, .style3-blog .blog-post.element .element-inner, .style4-blog .blog-post, .blog-post.format-link .element-inner, .blog-post.format-quote .element-inner, .woocommerce ul.products li.product, .woocommerce-page ul.products li.product, .chosen-container.chosen-container-single .chosen-drop, .chosen-container.chosen-container-single .chosen-single, .chosen-container.chosen-container-active.chosen-with-drop .chosen-single { color: #7a7a7a; } .woocommerce .quantity .plus, .woocommerce .quantity .minus, .woocommerce #content .quantity .plus, .woocommerce #content .quantity .minus, .woocommerce-page .quantity .plus, .woocommerce-page .quantity .minus, .woocommerce-page #content .quantity .plus, .woocommerce-page #content .quantity .minus, .woocommerce .quantity input.qty, .woocommerce #content .quantity input.qty, .woocommerce-page .quantity input.qty, .woocommerce-page #content .quantity input.qty { background: #fafbfd; color: #7a7a7a; border-color: #eeeeee; } .woocommerce div.product .woocommerce-tabs ul.tabs li, .woocommerce #content div.product .woocommerce-tabs ul.tabs li, .woocommerce-page div.product .woocommerce-tabs ul.tabs li, .woocommerce-page #content div.product .woocommerce-tabs ul.tabs li { color: #7a7a7a!important; } .chosen-container .chosen-drop, nav.woocommerce-pagination, .summary.entry-summary .price, .portfolio-details.style2 .gallery-side-heading-wrap, #single-author-info, .single-page-atts, article.comment { border-color: #eeeeee !important; } .fixed-sidebar-page #page-content{ background: #ffffff; } .sec-border, input[type="text"], input[type="email"], input[type="tel"], input[type="password"], textarea { border: 2px solid #eeeeee; } .chosen-container.chosen-container-single .chosen-single, .chosen-container.chosen-container-active.chosen-with-drop .chosen-single { border: 2px solid #eeeeee; } .woocommerce table.shop_attributes th, .woocommerce-page table.shop_attributes th, .woocommerce table.shop_attributes td, .woocommerce-page table.shop_attributes td { border: none; border-bottom: 1px solid #eeeeee; padding-bottom: 5px; } .woocommerce .widget_price_filter .price_slider_wrapper .ui-widget-content, .woocommerce-page .widget_price_filter .price_slider_wrapper .ui-widget-content{ border: 1px solid #eeeeee; } .pricing-table .pricing-title, .chosen-container .chosen-results li { border-bottom: 1px solid #eeeeee; } .separator { border:0; height:1px; color: #eeeeee; background-color: #eeeeee; } .alt-color, li.ui-tabs-active h6 a, a, a:visited, .social_media_icons a:hover, .post-title a:hover, .fn a:hover, a.team_icons:hover, .recent-post-title a:hover, .widget_nav_menu ul li.current-menu-item a, .widget_nav_menu ul li.current-menu-item:before, .woocommerce ul.cart_list li a:hover, .woocommerce ul.product_list_widget li a:hover, .woocommerce-page ul.cart_list li a:hover, .woocommerce-page ul.product_list_widget li a:hover, .woocommerce-page .product-categories li a:hover, .woocommerce ul.products li.product .product-meta-data h3:hover, .woocommerce table.cart a.remove:hover, .woocommerce #content table.cart a.remove:hover, .woocommerce-page table.cart a.remove:hover, .woocommerce-page #content table.cart a.remove:hover, td.product-name a:hover, .woocommerce-page #content .quantity .plus:hover, .woocommerce-page #content .quantity .minus:hover, .post-category a:hover, a.custom-like-button.liked, .menu-card-item-stared { color: #00bcdd; } .content-slide-wrap .flex-control-paging li a.flex-active, .content-slide-wrap .flex-control-paging li.flex-active a:before { background: #00bcdd !important; border-color: #00bcdd !important; } #navigation .menu > ul > li.mega > ul > li { border-color: #3d3d3d; } .sb-slidebar.sb-right .menu{ border-top: 1px solid #2d2d2d; border-bottom: 1px solid #2d2d2d; } .post-title a:hover { color: #00bcdd !important; } .alt-bg, input[type="submit"], .tagcloud a:hover, .pagination a:hover, .widget_tag_cloud a:hover, .pagination .current, .trigger_load_more .be-button, .trigger_load_more .be-button:hover { background-color: #00bcdd; transition: 0.2s linear all; } .mejs-controls .mejs-time-rail .mejs-time-current , .mejs-controls .mejs-horizontal-volume-slider .mejs-horizontal-volume-current, .woocommerce span.onsale, .woocommerce-page span.onsale, .woocommerce a.add_to_cart_button.button.product_type_simple.added, .woocommerce-page .widget_shopping_cart_content .buttons a.button:hover, .woocommerce nav.woocommerce-pagination ul li span.current, .woocommerce nav.woocommerce-pagination ul li a:hover, .woocommerce nav.woocommerce-pagination ul li a:focus, .testimonial-flex-slider .flex-control-paging li a.flex-active, #back-to-top, .be-carousel-nav, .portfolio-carousel .owl-controls .owl-prev:hover, .portfolio-carousel .owl-controls .owl-next:hover, .owl-theme .owl-controls .owl-dot.active span, .owl-theme .owl-controls .owl-dot:hover span, .more-link.style3-button, .view-project-link.style3-button{ background: #00bcdd !important; } .single-page-nav-link.current-section-nav-link { background: #ffffff !important; } .view-project-link.style2-button, .single-page-nav-link.current-section-nav-link { border-color: #00bcdd !important; } .view-project-link.style2-button:hover { background: #00bcdd !important; color: #ffffff !important; } .tagcloud a:hover, .testimonial-flex-slider .flex-control-paging li a.flex-active, .testimonial-flex-slider .flex-control-paging li a { border-color: #00bcdd; } a.be-button.view-project-link, .more-link { border-color: #00bcdd; } .portfolio-container .thumb-bg { background-color: rgba(0,188,221,0.85); } .photostream_overlay, .be-button, .more-link.style3-button, .view-project-link.style3-button, button, input[type="button"], input[type="submit"], input[type="reset"] { background-color: #00bcdd; } input[type="file"]::-webkit-file-upload-button{ background-color: #00bcdd; } .alt-bg-text-color, input[type="submit"], .tagcloud a:hover, .pagination a:hover, .widget_tag_cloud a:hover, .pagination .current, .woocommerce nav.woocommerce-pagination ul li span.current, .woocommerce nav.woocommerce-pagination ul li a:hover, .woocommerce nav.woocommerce-pagination ul li a:focus, #back-to-top, .be-carousel-nav, .single_portfolio_close .font-icon, .single_portfolio_back .font-icon, .more-link.style3-button, .view-project-link.style3-button, .trigger_load_more a.be-button, .trigger_load_more a.be-button:hover, .portfolio-carousel .owl-controls .owl-prev:hover .font-icon, .portfolio-carousel .owl-controls .owl-next:hover .font-icon{ color: #ffffff; transition: 0.2s linear all; } .woocommerce .button.alt.disabled { background: #efefef !important; color: #a2a2a2 !important; border: none !important; cursor: not-allowed; } .be-button, input[type="button"], input[type="submit"], input[type="reset"], button { color: #ffffff; transition: 0.2s linear all; } input[type="file"]::-webkit-file-upload-button { color: #ffffff; transition: 0.2s linear all; } .button-shape-rounded #submit, .button-shape-rounded .style2-button.view-project-link, .button-shape-rounded .style3-button.view-project-link, .button-shape-rounded .style2-button.more-link, .button-shape-rounded .style3-button.more-link, .button-shape-rounded .contact_submit { border-radius: 3px; } .button-shape-circular .style2-button.view-project-link, .button-shape-circular .style3-button.view-project-link{ border-radius: 50px; padding: 17px 30px !important; } .button-shape-circular .style2-button.more-link, .button-shape-circular .style3-button.more-link{ border-radius: 50px; padding: 7px 30px !important; } .button-shape-circular .contact_submit, .button-shape-circular #submit{ border-radius: 50px; padding-left: 30px; padding-right: 30px; } .view-project-link.style4-button:hover::after{ border-color : #00bcdd; } .mfp-arrow{ color: #ffffff; transition: 0.2s linear all; -moz-transition: 0.2s linear all; -o-transition: 0.2s linear all; transition: 0.2s linear all; } .portfolio-title a { color: inherit; } .arrow-block .arrow_prev, .arrow-block .arrow_next, .arrow-block .flickity-prev-next-button { background-color: rgb(0,0,0);background-color: rgba(0,0,0,1);} .arrow-border .arrow_prev, .arrow-border .arrow_next, .arrow-border .flickity-prev-next-button { border: 1px solid #000000; } .gallery-info-box-wrap .arrow_prev .font-icon, .gallery-info-box-wrap .arrow_next .font-icon{ color: #ffffff; } .flickity-prev-next-button .arrow{ fill: #ffffff; } .arrow-block .arrow_prev:hover, .arrow-block .arrow_next:hover, .arrow-block .flickity-prev-next-button:hover { background-color: rgb(0,0,0);background-color: rgba(0,0,0,1);} .arrow-border .arrow_prev:hover, .arrow-border .arrow_next:hover, .arrow-border .flickity-prev-next-button:hover { border: 1px solid #000000; } .gallery-info-box-wrap .arrow_prev:hover .font-icon, .gallery-info-box-wrap .arrow_next:hover .font-icon{ color: #ffffff; } .flickity-prev-next-button:hover .arrow{ fill: #ffffff; } #back-to-top.layout-border, #back-to-top.layout-border-header-top { right: 50px; bottom: 50px; } .layout-border .fixed-sidebar-page #right-sidebar.active-fixed { right: 30px; } body.header-transparent.admin-bar .layout-border #header #header-inner-wrap.no-transparent.top-animate, body.sticky-header.admin-bar .layout-border #header #header-inner-wrap.no-transparent.top-animate { top: 62px; } body.header-transparent .layout-border #header #header-inner-wrap.no-transparent.top-animate, body.sticky-header .layout-border #header #header-inner-wrap.no-transparent.top-animate { top: 30px; } body.header-transparent.admin-bar .layout-border.layout-border-header-top #header #header-inner-wrap.no-transparent.top-animate, body.sticky-header.admin-bar .layout-border.layout-border-header-top #header #header-inner-wrap.no-transparent.top-animate { top: 32px; z-index: 15; } body.header-transparent .layout-border.layout-border-header-top #header #header-inner-wrap.no-transparent.top-animate, body.sticky-header .layout-border.layout-border-header-top #header #header-inner-wrap.no-transparent.top-animate { top: 0px; z-index: 15; } body.header-transparent .layout-border #header #header-inner-wrap.no-transparent #header-wrap, body.sticky-header .layout-border #header #header-inner-wrap.no-transparent #header-wrap { margin: 0px 30px; -webkit-box-sizing: border-box; -moz-box-sizing: border-box; box-sizing: border-box; position: relative; } .mfp-content.layout-border img { padding: 70px 0px 70px 0px; } body.admin-bar .mfp-content.layout-border img { padding: 102px 0px 70px 0px; } .mfp-content.layout-border .mfp-bottom-bar { margin-top: -60px; } body .mfp-content.layout-border .mfp-close { top: 30px; } body.admin-bar .mfp-content.layout-border .mfp-close { top: 62px; } pre { background-image: -webkit-repeating-linear-gradient(top, #FFFFFF 0px, #FFFFFF 30px, #fafbfd 24px, #fafbfd 56px); background-image: -moz-repeating-linear-gradient(top, #FFFFFF 0px, #FFFFFF 30px, #fafbfd 24px, #fafbfd 56px); background-image: -ms-repeating-linear-gradient(top, #FFFFFF 0px, #FFFFFF 30px, #fafbfd 24px, #fafbfd 56px); background-image: -o-repeating-linear-gradient(top, #FFFFFF 0px, #FFFFFF 30px, #fafbfd 24px, #fafbfd 56px); background-image: repeating-linear-gradient(top, #FFFFFF 0px, #FFFFFF 30px, #fafbfd 24px, #fafbfd 56px); display: block; line-height: 28px; margin-bottom: 50px; overflow: auto; padding: 0px 10px; border:1px solid #eeeeee; } .post-title a{ color: inherit; } /*Animated link Typography*/ .be-sidemenu, .special-header-menu a::before{ background-color: rgb(26,26,26);background-color: rgba(26,26,26,1);} /*For normal styles add the padding in top and bottom*/ .be-themes-layout-layout-border .be-sidemenu, .be-themes-layout-layout-border .be-sidemenu, .be-themes-layout-layout-border-header-top .be-sidemenu, .be-themes-layout-layout-border-header-top .be-sidemenu{ padding: 30px 0px; box-sizing: border-box; } /*For center-align and left-align overlay, add padding to all sides*/ .be-themes-layout-layout-border.overlay-left-align-menu .be-sidemenu, .be-themes-layout-layout-border.overlay-center-align-menu .be-sidemenu, .be-themes-layout-layout-border-header-top.overlay-left-align-menu .be-sidemenu, .be-themes-layout-layout-border-header-top.overlay-center-align-menu .be-sidemenu{ padding: 30px; box-sizing: border-box; } .be-themes-layout-layout-border-header-top .be-sidemenu{ padding-top: 0px; } body.perspective-left.perspectiveview, body.perspective-right.perspectiveview{ background-color: rgb(26,26,26);background-color: rgba(26,26,26,1);} body.left-header.perspective-right.perspectiveview{ background-color: rgb(8,8,8);background-color: rgba(8,8,8,0.90);} body.perspective-left .be-sidemenu, body.perspective-right .be-sidemenu{ background-color : transparent; } /*Portfolio navigation*/ .loader-style1-double-bounce1, .loader-style1-double-bounce2, .loader-style2-wrap, .loader-style3-wrap > div, .loader-style5-wrap .dot1, .loader-style5-wrap .dot2, #nprogress .bar { background: #00bcdd !important; } .loader-style4-wrap { border-top: 7px solid rgba(0, 188, 221 , 0.3); border-right: 7px solid rgba(0, 188, 221 , 0.3); border-bottom: 7px solid rgba(0, 188, 221 , 0.3); border-left-color: #00bcdd; } #nprogress .spinner-icon { border-top-color: #00bcdd !important; border-left-color: #00bcdd !important; } #nprogress .peg { box-shadow: 0 0 10px #00bcdd, 0 0 5px #00bcdd !important; } .style1 #navigation, .style3 #navigation, .style4 #navigation, .style5 #navigation, #header-controls-left, #header-controls-right, #header-wrap, .mobile-nav-controller-wrap, #left-header-mobile .header-cart-controls, .style6 #navigation-left-side, .style6 #navigation-right-side, .style7 #navigation{ line-height: 66px; } body.header-transparent #header-wrap #navigation, body.header-transparent #header-wrap #navigation-left-side, body.header-transparent #header-wrap #navigation-right-side, body.header-transparent #header-inner-wrap .header-controls, body.header-transparent #header-inner-wrap #header-controls-left, body.header-transparent #header-inner-wrap #header-controls-right, body.header-transparent #header-inner-wrap #header-wrap, body.header-transparent #header-inner-wrap .mobile-nav-controller-wrap { line-height: 66px; } body #header-inner-wrap.top-animate #navigation, body #header-inner-wrap.top-animate #navigation-left-side, body #header-inner-wrap.top-animate #navigation-right-side, body #header-inner-wrap.top-animate .header-controls, body #header-inner-wrap.top-animate #header-wrap, body #header-inner-wrap.top-animate #header-controls-right, body #header-inner-wrap.top-animate #header-controls-left { line-height: 66px; } .header-transparent #content.page-split-screen-left, .header-transparent #content.page-split-screen-right{ } #navigation-left-side { padding-right: 90.5px; } #navigation-right-side { padding-left: 90.5px; } #bbpress-forums li.bbp-body ul.forum, #bbpress-forums li.bbp-body ul.topic { border-top: 1px solid #eeeeee; } #bbpress-forums ul.bbp-lead-topic, #bbpress-forums ul.bbp-topics, #bbpress-forums ul.bbp-forums, #bbpress-forums ul.bbp-replies, #bbpress-forums ul.bbp-search-results { border: 1px solid #eeeeee; } #bbpress-forums li.bbp-header, #bbpress-forums li.bbp-footer, .menu-card-item.highlight-menu-item { background: #fafbfd; } #bbpress-forums .topic .bbp-topic-meta a:hover, .bbp-forum-freshness a:hover, .bbp-topic-freshness a:hover, .bbp-header .bbp-reply-content a:hover, .bbp-topic-tags a:hover, .bbp-breadcrumb a:hover, .bbp-forums-list a:hover { color: #00bcdd; } div.bbp-reply-header, .bar-style-related-posts-list, .menu-card-item { border-color: #eeeeee; } #evcal_list .eventon_list_event .evcal_desc span.evcal_event_title, .eventon_events_list .evcal_event_subtitle { padding-bottom: 10px !important; } .eventon_events_list .eventon_list_event .evcal_desc, .evo_pop_body .evcal_desc, #page-content p.evcal_desc { padding-left: 100px !important; } .evcal_evdata_row { background: #fafbfd !important; } .eventon_events_list .eventon_list_event .event_description { background: #fafbfd !important; border-color: #eeeeee !important; } .bordr, #evcal_list .bordb { border-color: #eeeeee !important; } 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url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TjASc2CsTKlA.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TjASc5CsTKlA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TjASc1CsTKlA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 300; font-display: swap; src: 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font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51S7ACc5CsTKlA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51S7ACc1CsTKlA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51S7ACc0CsTKlA.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51S7ACc6CsQ.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic3CsTKlA.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic-CsTKlA.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic2CsTKlA.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic5CsTKlA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic1CsTKlA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic0CsTKlA.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TzBic6CsQ.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc3CsTKlA.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc-CsTKlA.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc2CsTKlA.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc5CsTKlA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc1CsTKlA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc0CsTKlA.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: italic; font-weight: 900; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOjCnqEu92Fr1Mu51TLBCc6CsQ.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxFIzIFKw.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxMIzIFKw.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxEIzIFKw.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxLIzIFKw.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxHIzIFKw.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxGIzIFKw.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 100; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOkCnqEu92Fr1MmgVxIIzI.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fCRc4EsA.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fABc4EsA.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fCBc4EsA.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fBxc4EsA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fCxc4EsA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fChc4EsA.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 300; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmSU5fBBc4.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu72xKOzY.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu5mxKOzY.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu7mxKOzY.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu4WxKOzY.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu7WxKOzY.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu7GxKOzY.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 400; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOmCnqEu92Fr1Mu4mxK.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fCRc4EsA.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fABc4EsA.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* greek-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fCBc4EsA.woff2) format('woff2'); unicode-range: U+1F00-1FFF; } /* greek */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fBxc4EsA.woff2) format('woff2'); unicode-range: U+0370-0377, U+037A-037F, U+0384-038A, U+038C, U+038E-03A1, U+03A3-03FF; } /* vietnamese */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fCxc4EsA.woff2) format('woff2'); unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; } /* latin-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fChc4EsA.woff2) format('woff2'); unicode-range: U+0100-02BA, U+02BD-02C5, U+02C7-02CC, U+02CE-02D7, U+02DD-02FF, U+0304, U+0308, U+0329, U+1D00-1DBF, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20C0, U+2113, U+2C60-2C7F, U+A720-A7FF; } /* latin */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 500; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmEU9fBBc4.woff2) format('woff2'); unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; } /* cyrillic-ext */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmWUlfCRc4EsA.woff2) format('woff2'); unicode-range: U+0460-052F, U+1C80-1C8A, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; } /* cyrillic */ @font-face { font-family: 'Roboto'; font-style: normal; font-weight: 700; font-display: swap; src: url(https://fonts.gstatic.com/s/roboto/v32/KFOlCnqEu92Fr1MmWUlfABc4EsA.woff2) format('woff2'); unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; } /* 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class="etn-social"></div></div></div></div></div></div> <div class="schedule-list-1"><h3 class="etn-title etn-schedule-wrap-title"> All Sessions by ODSC Instructor</h3><div class="etn-row"><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 1 </span> <span class="schedule-head-date">10/29/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Advance LLMs - Agents, Parameter Efficient Fine-Tuning, and RAG</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">LLMs</span> <span class="secfocus">All Levels</span> </span> </span><p>The workshop explores advanced topics in Large Language Models (LLMs) across three detailed sections. The first segment delves into LangChain Agents, showcasing the integration of LLMs with external systems to execute complex actions. The second part, """"Parameterized Fine-Tuning,"""" explores fine-tuning LLMs for specific tasks. In the final section, participants dive into """"Retrieval-Augmented Generation (RAG),"""" understanding how it merges retrieval and generation models to enhance language processing tasks. The section also elaborates on indexing content in a Retrieval Question-Answering chain for efficient information retrieval and showcases the use of Chroma, a vector database, for storing and managing high-dimensional vector data. Practical exercises, such as working with the CNN/DailyMail dataset, configuring chains, and prompt engineering, are peppered throughout, providing a hands-on learning experience on utilizing OpenAI and LangChain frameworks to tackle real-world problems. This workshop is a rich blend of theoretical knowledge and practical skills, aimed at harnessing the power of LLMs for varied applications.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 0 </span> <span class="schedule-head-date">09/04/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to NLP</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">NLP</span> <span class="secfocus">Self Paced</span> </span> </span><p>Welcome to the Introduction to NLP workshop! In this workshop, you will learn the fundamentals of Natural Language Processing. From tokenization and stop word removal to advanced topics like deep learning and large language models, you will explore techniques for text preprocessing, word embeddings, classic machine learning, and cutting-edge NLP methods. Get ready to dive into the exciting world of NLP and its applications!</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to R</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <span class="secfocus">Self Paced</span> </span> </span><p>Dive into the world of R programming in this interactive workshop, designed to hone your data analysis and visualization skills. Begin with a walkthrough of the Colab interface, understanding cell manipulation and library utilization. Explore core R data structures like vectors, lists, and data frames, and learn data wrangling techniques to manipulate and analyze datasets. Grasp the basics of programming with iterations and function applications, transitioning into Exploratory Data Analysis (EDA) to derive insights from your data. Discover data visualization using ggplot2, unveiling the stories hidden within data. Lastly, get acquainted with RStudio, the robust Integrated Development Environment, enhancing your R programming journey. This workshop is your gateway to mastering R, catering to both novices and seasoned programmers.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to Machine Learning</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <span class="secfocus">Self Paced</span> </span> </span><p>This is a hands-on course that utilizes Jupyter Notebooks. The link below will allow you to either download the notebooks or run them directly if you have a Google Colab account, which you can sign up for free.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 0 </span> <span class="schedule-head-date">10/28/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to R</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <span class="secfocus">Self Paced</span> </span> </span><p>Dive into the world of R programming in this interactive workshop, designed to hone your data analysis and visualization skills. Begin with a walkthrough of the Colab interface, understanding cell manipulation and library utilization. Explore core R data structures like vectors, lists, and data frames, and learn data wrangling techniques to manipulate and analyze datasets. Grasp the basics of programming with iterations and function applications, transitioning into Exploratory Data Analysis (EDA) to derive insights from your data. Discover data visualization using ggplot2, unveiling the stories hidden within data. Lastly, get acquainted with RStudio, the robust Integrated Development Environment, enhancing your R programming journey. This workshop is your gateway to mastering R, catering to both novices and seasoned programmers.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title"> Fine Tuning Existing LLMs and Embedding Models</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">LLMs</span> <span class="secfocus">Self Paced</span> </span> </span><p>This workshop explores the importance of fine-tuning Language and Embedding Models (LLMs). It highlights how embedding models are used to map natural language to vectors, crucial for pipelines with multiple models to adapt to specific data nuances. An example demonstrates fine-tuning an embedding model for legal text. The notebook discusses existing solutions and the hardware considerations, emphasizing GPU usage for large data. The practical part of the notebook shows the fine-tuning process of the """"distilroberta-base"""" model from the SentenceTransformer library. It utilizes the QQP_triplets dataset from Quora for training, designed around semantic meaning. The notebook prepares the data, sets up a DataLoader, and employs Triplet Loss to encourage the model to map similar data points closely while distancing dissimilar ones. It concludes by mentioning the training duration and resources needed for further improvements.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">GenAI & LLMS: Building a Q&A Bot with LLMs, Vector Search, and LangChain</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="firstfocus">Generative AI</span> <span class="secfocus">Self Paced</span> </span> </span><p>The workshop notebook delves into building a Question and Answering Bot based on a fixed knowledge base, covering the integration of concepts discussed in earlier notebooks about LLMs (Large Language Models) and prompting. Initially, it introduces a high-level architecture focusing on vector search—a method to retrieve similar items based on vector representations. The notebook explains the steps involved in vector search including vector representation, indexing, querying, similarity measurement, and retrieval, detailing various technologies used for vector search such as vector libraries, vector databases, and vector plugins. The example utilizes an Open Source vector database, Chroma, to index data and uses state of the union text data for the exercise. The notebook then transitions into the practical implementation, illustrating how text data is loaded, chunked into smaller pieces for effective vector search, and mapped into numeric vectors using the MPNetModel from the SentenceTransformer library via HuggingFace. Following this, the focus shifts to text generation where Langchain Chains are introduced. Chains, as described, allow for more complex applications by chaining several steps and models together into pipelines. A RetrievalQA chain is used to build a Q&A Bot application which utilizes an OpenAI chat model for text generation.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to Math for Data Science</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <span class="secfocus">Self Paced</span> </span> </span><p>Mathematics forms the backbone of data science, providing the essential tools for understanding, analyzing, and extracting insights from data. This session offers a foundational overview of key mathematical concepts indispensable for data scientists. Participants will explore probability, statistics, linear algebra, and calculus, gaining a solid grasp of their applications in real-world data challenges.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">GenAI & LLMS: Introduction to Prompt Engineering</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="firstfocus">Generative AI</span> <span class="secfocus">Self Paced</span> </span> </span><p>This workshop on Prompt Engineering explores the pivotal role of prompts in guiding Large Language Models (LLMs) like ChatGPT to generate desired responses. It emphasizes how prompts provide context, control output style and tone, aid in precise information retrieval, offer task-specific guidance, and ensure ethical AI usage. Through practical examples, participants learn how varying prompts can yield diverse responses, highlighting the importance of well-crafted prompts in achieving relevant and accurate text generation. Additionally, the workshop introduces temperature control to balance creativity and coherence in model outputs, and showcases LangChain, a Python library, to simplify prompt construction. Participants are equipped with practical tools and techniques to harness the potential of prompt engineering effectively, enhancing their interaction with LLMs across various contexts and tasks.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 2 </span> <span class="schedule-head-date">09/06/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Advance LLMs - Agents, Parameter Efficient Fine-Tuning, and RAG</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">LLMs</span> <span class="secfocus">Self Paced</span> </span> </span><p>The workshop explores advanced topics in Large Language Models (LLMs) across three detailed sections. The first segment delves into LangChain Agents, showcasing the integration of LLMs with external systems to execute complex actions. The second part, """"Parameterized Fine-Tuning,"""" explores fine-tuning LLMs for specific tasks. In the final section, participants dive into """"Retrieval-Augmented Generation (RAG),"""" understanding how it merges retrieval and generation models to enhance language processing tasks. The section also elaborates on indexing content in a Retrieval Question-Answering chain for efficient information retrieval and showcases the use of Chroma, a vector database, for storing and managing high-dimensional vector data. Practical exercises, such as working with the CNN/DailyMail dataset, configuring chains, and prompt engineering, are peppered throughout, providing a hands-on learning experience on utilizing OpenAI and LangChain frameworks to tackle real-world problems. This workshop is a rich blend of theoretical knowledge and practical skills, aimed at harnessing the power of LLMs for varied applications.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title"> Fine Tuning Existing LLMs and Embedding Models</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">LLMs</span> <span class="secfocus">Self Paced</span> </span> </span><p>This workshop explores the importance of fine-tuning Language and Embedding Models (LLMs). It highlights how embedding models are used to map natural language to vectors, crucial for pipelines with multiple models to adapt to specific data nuances. An example demonstrates fine-tuning an embedding model for legal text. The notebook discusses existing solutions and the hardware considerations, emphasizing GPU usage for large data. The practical part of the notebook shows the fine-tuning process of the """"distilroberta-base"""" model from the SentenceTransformer library. It utilizes the QQP_triplets dataset from Quora for training, designed around semantic meaning. The notebook prepares the data, sets up a DataLoader, and employs Triplet Loss to encourage the model to map similar data points closely while distancing dissimilar ones. It concludes by mentioning the training duration and resources needed for further improvements.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to Prompt Engineering</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">LLMs</span> <span class="secfocus">Self Paced</span> </span> </span><p>This workshop on Prompt Engineering explores the pivotal role of prompts in guiding Large Language Models (LLMs) like ChatGPT to generate desired responses. It emphasizes how prompts provide context, control output style and tone, aid in precise information retrieval, offer task-specific guidance, and ensure ethical AI usage. Through practical examples, participants learn how varying prompts can yield diverse responses, highlighting the importance of well-crafted prompts in achieving relevant and accurate text generation. Additionally, the workshop introduces temperature control to balance creativity and coherence in model outputs, and showcases LangChain, a Python library, to simplify prompt construction. Participants are equipped with practical tools and techniques to harness the potential of prompt engineering effectively, enhancing their interaction with LLMs across various contexts and tasks.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 2 </span> <span class="schedule-head-date">04/24/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Retrieval-Augmented Generation (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>Retrieval-Augmented Generation (RAG) is a powerful natural language processing (NLP) architecture introduced in this workshop notebook. RAG combines retrieval and generation models, enhancing language understanding and generation tasks. It consists of a retrieval component, which efficiently searches vast text databases for relevant information, and a generation component, often based on Transformer models, capable of producing coherent responses based on retrieved context. RAG’s versatility extends to various NLP applications, including question answering and text summarization. Additionally, this notebook covers practical aspects such as indexing content, configuring RAG chains, and incorporating prompt engineering, offering a comprehensive introduction to harnessing RAG’s capabilities for NLP tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Parameter Efficient Fine tuning (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>For the next workshop, our focus will be on parameter-efficient fine-tuning (PEFT) techniques in the field of machine learning, specifically within the context of large neural language models like GPT or BERT. PEFT is a powerful approach that allows us to adapt these pre-trained models to specific tasks while minimizing additional parameter overhead. Instead of fine-tuning the entire massive model, PEFT introduces compact, task-specific parameters known as “adapters” into the pre-trained model’s architecture. These adapters enable the model to adapt to new tasks without significantly increasing its size. PEFT strikes a balance between model size and adaptability, making it a crucial technique for real-world applications where computational and memory resources are limited, while still maintaining competitive performance. In this workshop, we will delve into the different PEFT methods, such as additive, selective, re-parameterization, adapter-based, and soft prompt-based approaches, exploring their characteristics, benefits, and practical applications. We will also demonstrate how to implement PEFT using the Hugging Face PEFT library, showcasing its effectiveness in adapting large pre-trained language models to specific tasks. Join us to discover how PEFT can make state-of-the-art language models more accessible and practical for a wide range of natural language processing tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">LangChain Agents (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>The “LangChain Agents” workshop delves into the “Agents” component of the LangChain library, offering a deeper understanding of how LangChain integrates Large Language Models (LLMs) with external systems and tools to execute actions. This workshop builds on the concept of “chains,” which can link multiple LLMs to tackle various tasks like classification, text generation, code generation, and more. “Agents” enable LLMs to interact with external systems and tools, making informed decisions based on available options. The workshop explores the different types of agents, such as “Zero-shot ReAct,” “Structured input ReAct,” “OpenAI Functions,” “Conversational,” “Self ask with search,” “ReAct document store,” and “Plan-and-execute agents.” It provides practical code examples, including initializing LLMs, defining tools, creating agents, and demonstrates how these agents can answer questions using external APIs, offering participants a comprehensive overview of LangChain’s agent capabilities.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Fine Tuning an Existing LLM (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>The workshop explores the process of fine-tuning Large Language Models (LLMs) for Natural Language Processing (NLP) tasks. It highlights the motivations for fine-tuning, such as task adaptation, transfer learning, and handling low-data scenarios, using a Yelp Review dataset. The notebook employs the HuggingFace Transformers library, including tokenization with AutoTokenizer, data subset selection, and model choice (BERT-based model). Hyperparameter tuning, evaluation strategy, and metrics are introduced. It also briefly mentions DeepSpeed for optimization and Parameter Efficient Fine-Tuning (PEFT) for resource-efficient fine-tuning, providing a comprehensive introduction to fine-tuning LLMs for NLP tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Fine Tuning Embedding Models (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>This workshop explores the importance of fine-tuning Language and Embedding Models (LLMs). It highlights how embedding models are used to map natural language to vectors, crucial for pipelines with multiple models to adapt to specific data nuances. An example demonstrates fine-tuning an embedding model for legal text. The notebook discusses existing solutions and hardware considerations, emphasizing GPU usage for large data. The practical part of the notebook shows the fine-tuning process of the “distilroberta-base” model from the SentenceTransformer library. It utilizes the QQP_triplets dataset from Quora for training, designed around semantic meaning. The notebook prepares the data, sets up a DataLoader, and employs Triplet Loss to encourage the model to map similar data points closely while distancing dissimilar ones. It concludes by mentioning the training duration and resources needed for further improvements.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Prompt Engineering with OpenAI (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Prompt Engineering</span> </span> </span><p>This workshop on prompt engineering with OpenAI discussed best practices for utilizing OpenAI models. We will review how to separate instructions and context using special characters to help improve instruction clarity, context isolation, and enhances control over the generation process. The workshop also included code for installing the langchain library and demonstrated how to create prompts effectively, emphasizing the importance of clarity, specificity, and precision in prompts. Additionally, the workshop showed how to craft prompts for specific tasks, such as extracting entities from text. It provided templates for prompts and highlighted the significance of specifying the desired output format through examples for improved consistency and customization. Lastly, the workshop addressed the importance of using prompts as safety guardrails. It introduced prompts to mitigate hallucination and jailbreaking risks by instructing the model to generate well-supported and verifiable information, thereby promoting responsible and ethical use of language models.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 1 </span> <span class="schedule-head-date">04/23/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">SQL Primer Course (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span> </span><p>This SQL coding course teaches students the basics of Structured Query Language, which is a standard programming language used for managing and manipulating data and an essential tool in AI. The course covers topics such as database design and normalization, data wrangling, aggregate functions, subqueries, and join operations, and students will learn now to design and write SQL code to solve real-world problems. Upon completion, students will have a strong foundation in SQL and be able to use it effectively to extract insights from data. The ability to effectively access, retrieve, and manipulate data using SQL is essential for data cleaning, pre-processing, and exploration, which are crucial steps in any data science or machine learning project. Additionally, SQL is widely used in industry, making it a valuable skill for professionals in the field. This course builds upon the earlier data course in the series.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Prompt Engineering Fundamentals (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Prompt Engineering</span> </span> </span><p>This workshop on Prompt Engineering explores the pivotal role of prompts in guiding Large Language Models (LLMs) like ChatGPT to generate desired responses. It emphasizes how prompts provide context, control output style and tone, aid in precise information retrieval, offer task-specific guidance, and ensure ethical AI usage. Through practical examples, participants learn how varying prompts can yield diverse responses, highlighting the importance of well-crafted prompts in achieving relevant and accurate text generation. Additionally, the workshop introduces temperature control to balance creativity and coherence in model outputs, and showcases LangChain, a Python library, to simplify prompt construction. Participants are equipped with practical tools and techniques to harness the potential of prompt engineering effectively, enhancing their interaction with LLMs across various contexts and tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Build a Question & Answering Bot (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> </span> </span><p>The workshop notebook delves into building a Question and Answering Bot based on a fixed knowledge base, covering the integration of concepts discussed in earlier notebooks about LLMs (Large Language Models) and prompting. Initially, it introduces a high-level architecture focusing on vector search—a method to retrieve similar items based on vector representations. The notebook explains the steps involved in vector search including vector representation, indexing, querying, similarity measurement, and retrieval, detailing various technologies used for vector search such as vector libraries, vector databases, and vector plugins. The example utilizes an Open Source vector database, Chroma, to index data and uses state-of-the-union text data for the exercise. The notebook then transitions into the practical implementation, illustrating how text data is loaded, chunked into smaller pieces for effective vector search, and mapped into numeric vectors using the MPNetModel from the SentenceTransformer library via HuggingFace. Following this, the focus shifts to text generation where Langchain Chains are introduced. Chains, as described, allow for more complex applications by chaining several steps and models together into pipelines. A RetrievalQA chain is used to build a Q&A Bot application which utilizes an OpenAI chat model for text generation.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Data Wrangling with Python (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p </span> </span><p>Data wrangling is the cornerstone of any data-driven project, and Python stands as one of the most powerful tools in this domain. In preparation for the ODSC conference, our specially designed course on “Data Wrangling with Python” offers attendees a hands-on experience to master the essential techniques. From cleaning and transforming raw data to making it ready for analysis, this course will equip you with the skills needed to handle real-world data challenges. As prat of a comprehensive series leading up to the conference, this course not only lays the foundation for more advanced AI topics but also aligns with the industry’s most popular coding language. Upon completion of this short course, attendees will be fully equipped with the knowledge and skills to manage the data lifecycle and turn raw data into actionable insights, setting the stage for advanced data analysis and AI applications.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 0 </span> <span class="schedule-head-date">04/22/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Data Primer Course (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span> </span><p>Data is the essential building block of Data Science, Machine Learning and AI. This course is the first in the series and is designed to teach you the foundational skills and knowledge required to understand, work with, and analyze data. It covers topics such as data collection, organization, profiling, and transformation as well as basic analysis. The course is aimed at helping people begin their AI journey and gain valuable insights that we will build up in subsequent SQL, programming, and AI courses.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to R</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span> </span><p>Dive into the world of R programming in this interactive workshop, designed to hone your data analysis and visualization skills. Begin with a walkthrough of the Colab interface, understanding cell manipulation and library utilization. Explore core R data structures like vectors, lists, and data frames, and learn data wrangling techniques to manipulate and analyze datasets. Grasp the basics of programming with iterations and function applications, transitioning into Exploratory Data Analysis (EDA) to derive insights from your data. Discover data visualization using ggplot2, unveiling the stories hidden within data. Lastly, get acquainted with RStudio, the robust Integrated Development Environment, enhancing your R programming journey. This workshop is your gateway to mastering R, catering to both novices and seasoned programmers.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to AI (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span> </span><p>This AI literacy course is designed to introduce participants to the basics of artificial intelligence (AI) and machine learning. We will first explore the various types of AI and then progress to understand fundamental concepts such as algorithms, features, and models. We will study the machine learning workflow and how it is used to design, build, and deploy models that can learn from data to make predictions. This will cover model training and types of machine learning including supervised, and unsupervised learning, as well as some of the most common models such as regression and k-means clustering. Upon completion, individuals will have foundational understanding of machine learning and its capabilities and be well-positioned to take advantage of introductory-level hands-on training in machine learning and data science such as ODSDC East’s Mini-Bootcamp.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to NLP</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Natural Language Processing</span> </span> </span><p>Welcome to the Introduction to NLP workshop! In this workshop, you will learn the fundamentals of Natural Language Processing. From tokenization and stop word removal to advanced topics like deep learning and large language models, you will explore techniques for text preprocessing, word embeddings, classic machine learning, and cutting-edge NLP methods. Get ready to dive into the exciting world of NLP and its applications!</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to Large Language Models</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This hands-on course serves as a comprehensive introduction to Large Language Models (LLMs), covering a spectrum of topics from their differentiation from other language models to their underlying architecture and practical applications. It delves into the technical aspects, such as the transformer architecture and the attention mechanism, which are the cornerstones of modern language models. The course also explores the applications of LLMs, focusing on zero-shot learning, few-shot learning, and fine-tuning, which showcase the models’ ability to adapt and perform tasks with limited to no examples. Furthermore, it introduces the concept of flow chaining as a method to generate coherent and extended text, demonstrating its usefulness in tackling token limitations in real-world scenarios such as Q&A bots. Through practical examples and code snippets, participants are given a hands-on experience on how to utilize and harness the power of LLMs across various domains. By utilizing the code notebooks included in this course, participants can code alongside the code instructor to ensure hands-on practice experience in LLMs</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 0 </span> <span class="schedule-head-date">04/22/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Data Primer Course (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>Data is the essential building block of Data Science, Machine Learning and AI. This course is the first in the series and is designed to teach you the foundational skills and knowledge required to understand, work with, and analyze data. It covers topics such as data collection, organization, profiling, and transformation as well as basic analysis. The course is aimed at helping people begin their AI journey and gain valuable insights that we will build up in subsequent SQL, programming, and AI courses.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to Large Language Models</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This hands-on course serves as a comprehensive introduction to Large Language Models (LLMs), covering a spectrum of topics from their differentiation from other language models to their underlying architecture and practical applications. It delves into the technical aspects, such as the transformer architecture and the attention mechanism, which are the cornerstones of modern language models. The course also explores the applications of LLMs, focusing on zero-shot learning, few-shot learning, and fine-tuning, which showcase the models’ ability to adapt and perform tasks with limited to no examples. Furthermore, it introduces the concept of flow chaining as a method to generate coherent and extended text, demonstrating its usefulness in tackling token limitations in real-world scenarios such as Q&A bots. Through practical examples and code snippets, participants are given a hands-on experience on how to utilize and harness the power of LLMs across various domains. By utilizing the code notebooks included in this course, participants can code alongside the code instructor to ensure hands-on practice experience in LLMs</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to NLP</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Natural Language Processing</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>Welcome to the Introduction to NLP workshop! In this workshop, you will learn the fundamentals of Natural Language Processing. From tokenization and stop word removal to advanced topics like deep learning and large language models, you will explore techniques for text preprocessing, word embeddings, classic machine learning, and cutting-edge NLP methods. Get ready to dive into the exciting world of NLP and its applications!</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to R</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>Dive into the world of R programming in this interactive workshop, designed to hone your data analysis and visualization skills. Begin with a walkthrough of the Colab interface, understanding cell manipulation and library utilization. Explore core R data structures like vectors, lists, and data frames, and learn data wrangling techniques to manipulate and analyze datasets. Grasp the basics of programming with iterations and function applications, transitioning into Exploratory Data Analysis (EDA) to derive insights from your data. Discover data visualization using ggplot2, unveiling the stories hidden within data. Lastly, get acquainted with RStudio, the robust Integrated Development Environment, enhancing your R programming journey. This workshop is your gateway to mastering R, catering to both novices and seasoned programmers.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Introduction to AI (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This AI literacy course is designed to introduce participants to the basics of artificial intelligence (AI) and machine learning. We will first explore the various types of AI and then progress to understand fundamental concepts such as algorithms, features, and models. We will study the machine learning workflow and how it is used to design, build, and deploy models that can learn from data to make predictions. This will cover model training and types of machine learning including supervised, and unsupervised learning, as well as some of the most common models such as regression and k-means clustering. Upon completion, individuals will have foundational understanding of machine learning and its capabilities and be well-positioned to take advantage of introductory-level hands-on training in machine learning and data science such as ODSDC East’s Mini-Bootcamp.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 2 </span> <span class="schedule-head-date">04/24/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Retrieval-Augmented Generation (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>Retrieval-Augmented Generation (RAG) is a powerful natural language processing (NLP) architecture introduced in this workshop notebook. RAG combines retrieval and generation models, enhancing language understanding and generation tasks. It consists of a retrieval component, which efficiently searches vast text databases for relevant information, and a generation component, often based on Transformer models, capable of producing coherent responses based on retrieved context. RAG’s versatility extends to various NLP applications, including question answering and text summarization. Additionally, this notebook covers practical aspects such as indexing content, configuring RAG chains, and incorporating prompt engineering, offering a comprehensive introduction to harnessing RAG’s capabilities for NLP tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Parameter Efficient Fine tuning (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>For the next workshop, our focus will be on parameter-efficient fine-tuning (PEFT) techniques in the field of machine learning, specifically within the context of large neural language models like GPT or BERT. PEFT is a powerful approach that allows us to adapt these pre-trained models to specific tasks while minimizing additional parameter overhead. Instead of fine-tuning the entire massive model, PEFT introduces compact, task-specific parameters known as “adapters” into the pre-trained model’s architecture. These adapters enable the model to adapt to new tasks without significantly increasing its size. PEFT strikes a balance between model size and adaptability, making it a crucial technique for real-world applications where computational and memory resources are limited, while still maintaining competitive performance. In this workshop, we will delve into the different PEFT methods, such as additive, selective, re-parameterization, adapter-based, and soft prompt-based approaches, exploring their characteristics, benefits, and practical applications. We will also demonstrate how to implement PEFT using the Hugging Face PEFT library, showcasing its effectiveness in adapting large pre-trained language models to specific tasks. Join us to discover how PEFT can make state-of-the-art language models more accessible and practical for a wide range of natural language processing tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">LangChain Agents (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>The “LangChain Agents” workshop delves into the “Agents” component of the LangChain library, offering a deeper understanding of how LangChain integrates Large Language Models (LLMs) with external systems and tools to execute actions. This workshop builds on the concept of “chains,” which can link multiple LLMs to tackle various tasks like classification, text generation, code generation, and more. “Agents” enable LLMs to interact with external systems and tools, making informed decisions based on available options. The workshop explores the different types of agents, such as “Zero-shot ReAct,” “Structured input ReAct,” “OpenAI Functions,” “Conversational,” “Self ask with search,” “ReAct document store,” and “Plan-and-execute agents.” It provides practical code examples, including initializing LLMs, defining tools, creating agents, and demonstrates how these agents can answer questions using external APIs, offering participants a comprehensive overview of LangChain’s agent capabilities.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Fine Tuning an Existing LLM (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>The workshop explores the process of fine-tuning Large Language Models (LLMs) for Natural Language Processing (NLP) tasks. It highlights the motivations for fine-tuning, such as task adaptation, transfer learning, and handling low-data scenarios, using a Yelp Review dataset. The notebook employs the HuggingFace Transformers library, including tokenization with AutoTokenizer, data subset selection, and model choice (BERT-based model). Hyperparameter tuning, evaluation strategy, and metrics are introduced. It also briefly mentions DeepSpeed for optimization and Parameter Efficient Fine-Tuning (PEFT) for resource-efficient fine-tuning, providing a comprehensive introduction to fine-tuning LLMs for NLP tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Fine Tuning Embedding Models (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This workshop explores the importance of fine-tuning Language and Embedding Models (LLMs). It highlights how embedding models are used to map natural language to vectors, crucial for pipelines with multiple models to adapt to specific data nuances. An example demonstrates fine-tuning an embedding model for legal text. The notebook discusses existing solutions and hardware considerations, emphasizing GPU usage for large data. The practical part of the notebook shows the fine-tuning process of the “distilroberta-base” model from the SentenceTransformer library. It utilizes the QQP_triplets dataset from Quora for training, designed around semantic meaning. The notebook prepares the data, sets up a DataLoader, and employs Triplet Loss to encourage the model to map similar data points closely while distancing dissimilar ones. It concludes by mentioning the training duration and resources needed for further improvements.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Prompt Engineering with OpenAI (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Prompt Engineering</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This workshop on prompt engineering with OpenAI discussed best practices for utilizing OpenAI models. We will review how to separate instructions and context using special characters to help improve instruction clarity, context isolation, and enhances control over the generation process. The workshop also included code for installing the langchain library and demonstrated how to create prompts effectively, emphasizing the importance of clarity, specificity, and precision in prompts. Additionally, the workshop showed how to craft prompts for specific tasks, such as extracting entities from text. It provided templates for prompts and highlighted the significance of specifying the desired output format through examples for improved consistency and customization. Lastly, the workshop addressed the importance of using prompts as safety guardrails. It introduced prompts to mitigate hallucination and jailbreaking risks by instructing the model to generate well-supported and verifiable information, thereby promoting responsible and ethical use of language models.</p></div></div></div></div><div class="etn-col-lg-6"><div class="etn-schedule-wrap"><div class="schedule-header"> <span class="schedule-head-title"> Day 1 </span> <span class="schedule-head-date">04/23/2024</span></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">SQL Primer Course (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This SQL coding course teaches students the basics of Structured Query Language, which is a standard programming language used for managing and manipulating data and an essential tool in AI. The course covers topics such as database design and normalization, data wrangling, aggregate functions, subqueries, and join operations, and students will learn now to design and write SQL code to solve real-world problems. Upon completion, students will have a strong foundation in SQL and be able to use it effectively to extract insights from data. The ability to effectively access, retrieve, and manipulate data using SQL is essential for data cleaning, pre-processing, and exploration, which are crucial steps in any data science or machine learning project. Additionally, SQL is widely used in industry, making it a valuable skill for professionals in the field. This course builds upon the earlier data course in the series.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Data Wrangling with Python (Self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>Data wrangling is the cornerstone of any data-driven project, and Python stands as one of the most powerful tools in this domain. In preparation for the ODSC conference, our specially designed course on “Data Wrangling with Python” offers attendees a hands-on experience to master the essential techniques. From cleaning and transforming raw data to making it ready for analysis, this course will equip you with the skills needed to handle real-world data challenges. As prat of a comprehensive series leading up to the conference, this course not only lays the foundation for more advanced AI topics but also aligns with the industry’s most popular coding language. Upon completion of this short course, attendees will be fully equipped with the knowledge and skills to manage the data lifecycle and turn raw data into actionable insights, setting the stage for advanced data analysis and AI applications.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Prompt Engineering Fundamentals (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Prompt Engineering</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>This workshop on Prompt Engineering explores the pivotal role of prompts in guiding Large Language Models (LLMs) like ChatGPT to generate desired responses. It emphasizes how prompts provide context, control output style and tone, aid in precise information retrieval, offer task-specific guidance, and ensure ethical AI usage. Through practical examples, participants learn how varying prompts can yield diverse responses, highlighting the importance of well-crafted prompts in achieving relevant and accurate text generation. Additionally, the workshop introduces temperature control to balance creativity and coherence in model outputs, and showcases LangChain, a Python library, to simplify prompt construction. Participants are equipped with practical tools and techniques to harness the potential of prompt engineering effectively, enhancing their interaction with LLMs across various contexts and tasks.</p></div></div><div class="etn-single-schedule-item"><div class="etn-schedule-content"><h4 class="etn-title">Build a Question & Answering Bot (self-paced)</h4> <span class="etn-schedule-location"> <i class="etn-icon etn-location"></i> <span class="etn-schedule-location"> <span class="firstfocus">Large Language Models</span> <p class="locationvirtlive">Virtual conference</p> </span> </span><p>The workshop notebook delves into building a Question and Answering Bot based on a fixed knowledge base, covering the integration of concepts discussed in earlier notebooks about LLMs (Large Language Models) and prompting. Initially, it introduces a high-level architecture focusing on vector search—a method to retrieve similar items based on vector representations. The notebook explains the steps involved in vector search including vector representation, indexing, querying, similarity measurement, and retrieval, detailing various technologies used for vector search such as vector libraries, vector databases, and vector plugins. The example utilizes an Open Source vector database, Chroma, to index data and uses state-of-the-union text data for the exercise. The notebook then transitions into the practical implementation, illustrating how text data is loaded, chunked into smaller pieces for effective vector search, and mapped into numeric vectors using the MPNetModel from the SentenceTransformer library via HuggingFace. Following this, the focus shifts to text generation where Langchain Chains are introduced. Chains, as described, allow for more complex applications by chaining several steps and models together into pipelines. A RetrievalQA chain is used to build a Q&A Bot application which utilizes an OpenAI chat model for text generation.</p></div></div></div></div></div></div></div></div></div><footer id="bottom-widgets"><div id="bottom-widgets-wrap" class="be-wrap be-row clearfix"><div class="one-fourth column-block clearfix"><div class="widget_text widget"><h6>Open Data Science</h6><div class="textwidget"><div class="textwidget"><div class="tatsu-module tatsu-normal-icon tatsu-icon-shortcode align-none tatsu-goka2it139bzrcg7 "> <style>.tatsu-goka2it139bzrcg7 .tatsu-icon{background-color: #00aced;color: #ffffff ;border-color: #ffffff; }.tatsu-goka2it139bzrcg7 .tatsu-icon:hover{background-color: #00aced;color: #ffffff ;}</style><p> </p></div><div class="tatsu-module tatsu-normal-icon tatsu-icon-shortcode align-none tatsu-goka2it16zd3n28v "> <style>.tatsu-goka2it16zd3n28v .tatsu-icon{background-color: #3B5998;color: #ffffff ;border-color: #ffffff; }.tatsu-goka2it16zd3n28v .tatsu-icon:hover{background-color: #3B5998;color: #ffffff ;}</style><p> </p></div><div class="tatsu-module tatsu-normal-icon tatsu-icon-shortcode align-none tatsu-goka2it19262p6uh "> <style>.tatsu-goka2it19262p6uh .tatsu-icon{background-color: #bb0000;color: #ffffff ;border-color: #ffffff; }.tatsu-goka2it19262p6uh .tatsu-icon:hover{background-color: #bb0000;color: #ffffff ;}</style><p> </p></div><p>Open Data Science<br /> One Broadway<br /> Cambridge, MA 02142<br /> info@odsc.com</p></div></div></div></div><div class="one-fourth column-block clearfix"><div class="widget_nav_menu widget"><h6>Menu</h6><div class="menu-footer_nav-container"><ul id="menu-footer_nav" class="menu"><li id="menu-item-34705" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-34705"><a href="/boston/partner-odsc-east/" title="Partner with ODSC">Partner with ODSC</a></li><li id="menu-item-1656" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-1656"><a href="https://www.opendatascience.com/" title="Blog">Blog</a></li><li id="menu-item-1657" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-1657"><a href="https://aiplus.training/" title="Training">Training</a></li><li id="menu-item-1655" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-1655"><a href="https://jobs.opendatascience.com/" title="Jobs">Jobs</a></li><li id="menu-item-14010" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-14010"><a href="https://odsc.com/faq/" title="FAQ">FAQ</a></li></ul></div></div></div><div class="one-fourth column-block clearfix"><div class="widget_nav_menu widget"><h6>Conferences</h6><div class="menu-conf_footer-container"><ul id="menu-conf_footer" class="menu"><li id="menu-item-27912" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-27912"><a href="/boston/" title="East 2025">East 2025</a></li><li id="menu-item-45631" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-45631"><a href="/europe/" title="Europe 2025">Europe 2025</a></li><li id="menu-item-19688" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-19688"><a href="/apac/" title="APAC 2025">APAC 2025</a></li><li id="menu-item-1661" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-1661"><a href="/california/" title="West 2025">West 2025</a></li></ul></div></div></div><div class="one-fourth column-block clearfix"><div class="widget_nav_menu widget"><h6>Extras</h6><div class="menu-extras-container"><ul id="menu-extras" class="menu"><li id="menu-item-1663" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-1663"><a href="https://opendatascience.com/newsletter/?__hstc=19222759.9747cccda111769b206e3552831bc327.1533925250574.1535328146852.1535383810113.51&__hssc=19222759.10.1535383810113&__hsfp=1117387146" title="Newsletter">Newsletter</a></li><li id="menu-item-58125" class="menu-item menu-item-type-custom menu-item-object-custom menu-item-58125"><a href="/about-open-data-science-conference/" title="About">About</a></li><li id="menu-item-1666" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-1666"><a href="https://odsc.com/code-of-conduct/" title="Code of Conduct">Code of Conduct</a></li><li id="menu-item-1667" class="menu-item menu-item-type-post_type menu-item-object-page menu-item-1667"><a href="https://odsc.com/privacy-policy/" title="Privacy Policy">Privacy Policy</a></li></ul></div></div></div></div></footer><footer id="footer" class="layout-wide"> <span class="footer-border "></span><div id="footer-wrap" class=" style1 clearfix"><div class="footer-left-area"></div><div class="footer-center-area"><div class="footer-content-inner-center"> Copyright ODSC 2024. 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// Define the div for the tooltip let tooltip = d3.select("body").append("div") .attr("class", "tooltip") .style("opacity", 0); let nodeId = 0; let root; let tree = d3.layout.tree() .size([viewerHeight, viewerWidth]); // define a d3 diagonal projection for use by the node paths later on. const diagonal = d3.svg.diagonal() .projection(d => [d.y, d.x]); // Define the zoom function for the zoomable tree function zoom() { svgGroup.attr("transform", "translate(" + d3.event.translate + ")scale(" + d3.event.scale + ")"); } // define the zoomListener which calls the zoom function on the "zoom" event constrained within the scaleExtents const zoomListener = d3.behavior.zoom().scaleExtent([0.1, 3]).on("zoom", zoom); // define the baseSvg, attaching a class for styling and the zoomListener const baseSvg = d3.select("#tree-container").append("svg") .attr("width", viewerWidth) .attr("height", viewerHeight) .attr("class", "overlay") .on("mousemove", (d) => mouseOut(d)); // Function to collapse node function collapse(d) { if (d.children) { d._children = d.children; d._children.forEach(collapse); d.children = null; } } // Function to center node when clicked/dropped so node doesn't get lost when collapsing/moving with large amount of children. function centerNode(source) { let scale = zoomListener.scale(); let x = -source.y0; let y = -source.x0; x = x * scale + viewerWidth / 2; y = y * scale + viewerHeight / 2; d3.select('g').transition() .duration(duration) .attr("transform", "translate(" + x + "," + y + ")scale(" + scale + ")"); zoomListener.scale(scale); zoomListener.translate([x, y]); } // Toggle children function function toggleChildren(d) { if (d.children) { d._children = d.children; d.children = null; } else if (d._children) { d.children = d._children; d._children = null; } return d; } // Toggle children on click. function click(d) { if (d3.event.defaultPrevented) { return; } d = toggleChildren(d); update(d); if (d.children || d._children) { centerNode(d); } if (d.depth === 0) { if (d.children) { baseSvg.call(zoomListener); } else { baseSvg.on('.zoom', null); } } } // Get width of text function measureWidth(text) { const context = document.createElement("canvas").getContext("2d"); return context.measureText(text).width; } // Split string into words function splitWords(text, node) { const words = text.split(/\s+/g); // To hyphenate: /\s+|(?<=-)/ if (!words[words.length - 1]) { words.pop(); } else if (!words[0]) { words.shift(); } return { words, node }; } // Get lines from text when it overflows maxTextWidth function getLines(node) { let line; let lineWidth0 = Infinity; let lines = []; for (let i = 0, n = node.words.length; i < n; ++i) { let lineText1 = (line ? line.text + " " : "") + node.words[i]; let lineWidth1 = measureWidth(lineText1); if ((lineWidth0 + lineWidth1) / 2 < maxTextWith) { line.width = lineWidth0 = lineWidth1; line.text = lineText1; } else { lineWidth0 = measureWidth(node.words[i]); line = { width: lineWidth0, text: node.words[i], ...node.node, length: lines.length }; lines.push(line); } } return lines; } function mouseOver(d) { if (!d["Level"]) { return; } let html = ""; if (d["URL"]) { html += `<a target="_blank" rel="noopener">Course Link</a>`; } html += `<p><strong>Level: </strong>${d["Level"]}</p>`; if (d["Type"]) { html += `<p><strong>Type: </strong>${d["Type"]}</p>`; } if (d["Duration"]) { html += `<p><strong>Duration: </strong>${d["Duration"]}</p>`; } tooltip.transition() .duration(200) .style("opacity", .9); tooltip.html(html) .style("left", (d3.event.pageX) + "px") .style("top", (d3.event.pageY) + "px"); hoveredPosition = { x: d3.event.pageX, y: d3.event.pageY }; } function mouseOut(d) { if (hoveredPosition.x === 0 || (d3.event.pageX > hoveredPosition.x - 10 && d3.event.pageX < hoveredPosition.x + 150 && d3.event.pageY > hoveredPosition.y - 10 && d3.event.pageY < hoveredPosition.y + 90)) { return; } tooltip.transition() .duration(500) .style("opacity", 0); tooltip.html(null); } function update(source) { // Compute the new height, function counts total children of root node and sets tree height accordingly. // This prevents the layout looking squashed when new nodes are made visible or looking sparse when nodes are removed // This makes the layout more consistent. let levelWidth = [1]; const childCount = (level, n) => { if (n.children && n.children.length > 0) { if (levelWidth.length <= level + 1) { levelWidth.push(0); } levelWidth[level + 1] += n.children.length; n.children.forEach((d) => { childCount(level + 1, d); }); } }; childCount(0, root); const newHeight = d3.max(levelWidth) * (25 + (source.depth ? source.depth * 5 : 0)); // 25 pixels per line tree = tree.size([newHeight, viewerWidth]); // Compute the new tree layout. const nodes = tree.nodes(root).reverse(), links = tree.links(nodes); // Set widths between levels based on maxLabelLength. nodes.forEach((d) => { d.y = (d.depth * 300); d.x = d.x * 2.5; }); // Update the nodes… node = svgGroup.selectAll("g.node") .data(nodes, (d) => { return d.id || (d.id = ++nodeId); }); // Enter any new nodes at the parent's previous position. let nodeEnter = node.enter().append("g") .attr("class", "node") .attr("transform", (d) => { return "translate(" + source.y0 + "," + source.x0 + ")"; }) .on('click', click); nodeEnter.append("circle") .attr('class', 'nodeCircle') .attr("r", 0) .style("fill", (d) => { return d._children ? (d.color || "lightsteelblue") : "#fff"; }); let rect = nodeEnter.append("rect") .attr('class', 'nodeRect') .attr('x', (d) => 5) .attr('y', (d) => { return d.children || d._children ? 0 : -12 - getLines(splitWords(d.name, d)).length * 2; }) .attr('width', (d) => { return d.children || d._children ? 0 : 240; }) .attr('height', (d) => { return d.children || d._children ? 0 : getLines(splitWords(d.name, d)).length * 18; }) .attr('stroke', '#fff') .attr('fill', 'transparent') .attr('rx', 10); nodeEnter.append("text") .attr('class', 'nodeText') .attr("text-anchor", (d) => { return d.children || d._children ? "end" : "start"; }) .style("fill", (d) => { return d.children || d._children ? "#ddd" : "#fff"; }) .style("fill-opacity", 0) .on("mouseover", (d) => mouseOver(d)) .selectAll("tspan") .data(d => getLines(splitWords(d.name, d))) .enter() .append("tspan") .attr("x", (d) => { return d.children || d._children ? -8 : 8; }) .attr("y", (d, i) => i * lineHeight) .attr("dy", d => { if (d.children || d._children) { return '-1.2em'; } return '0em'; }) .text(d => d.text); // Change the circle fill depending on whether it has children and is collapsed node.select("circle.nodeCircle") .attr("r", d => { let maxChildLength = 0; if (d.children || d._children) { (d.children || d._children).forEach(c => { if ((c.children || c._children) && (c.children || c._children).length > maxChildLength) { maxChildLength = (c.children || c._children).length; } }); if ((d.children || d._children).length > maxChildLength) { maxChildLength = (d.children || d._children).length; } if (maxChildLength < 4) { maxChildLength = 4; } } else { maxChildLength = 1.5; } return (maxChildLength * 3 / 2) + "px"; }) .style("fill", (d) => { return d._children ? (d.color || "green") : "#fff"; }); // Transition nodes to their new position. let nodeUpdate = node.transition() .duration(duration) .attr("transform", (d) => { return "translate(" + d.y + "," + d.x + ")"; }); // Fade the text in nodeUpdate.select("text") .style("fill-opacity", 1); // Transition exiting nodes to the parent's new position. let nodeExit = node.exit().transition() .duration(duration) .attr("transform", (d) => { return "translate(" + source.y + "," + source.x + ")"; }) .remove(); nodeExit.select("circle") .attr("r", 0); nodeExit.select("text") .style("fill-opacity", 0); // Update the links… let link = svgGroup.selectAll("path.link") .data(links, (d) => { return d.target.id; }); // Enter any new links at the parent's previous position. link.enter().insert("path", "g") .attr("class", "link") .attr("stroke-width", d => { if (d.target.children || d.target._children) { return (d.target.children || d.target._children).length * 3 + "px"; } return "2px"; }) .attr("stroke", d => d.target.color || "#ccc") .attr("d", (d) => { const o = { x: source.x0, y: source.y0 }; return diagonal({ source: o, target: o }); }); // Transition links to their new position. link.transition() .duration(duration) .attr("d", diagonal); // Transition exiting nodes to the parent's new position. link.exit().transition() .duration(duration) .attr("d", (d) => { const o = { x: source.x, y: source.y }; return diagonal({ source: o, target: o }); }) .remove(); // Stash the old positions for transition. nodes.forEach((d) => { d.x0 = d.x; d.y0 = d.y; }); } // Append a group which holds all nodes and which the zoom Listener can act upon. let svgGroup = baseSvg.append("g"); // Define the root root = JSON.parse(JSON.stringify(data)); root.x0 = viewerHeight / 2; root.y0 = 0; // Layout the tree initially and center on the root node. collapse(root); update(root); centerNode(root); } drawChart(treeData); window.addEventListener('resize', () => { drawChart(treeData); });</script> <div id='icon_wrapper'><a target="_blank" class='fuse_social_icons_links' href='https://www.facebook.com/OPENDATASCI'> <i class='fa fa-facebook fb-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='https://twitter.com/_odsc'> <i class='fa-brands fa-x-twitter tw-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='https://www.linkedin.com/company/open-data-science/'> <i class='fa fa-linkedin linkedin-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='https://www.youtube.com/c/OpenDataScienceCon'> <i class='fa fa-youtube youtube-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='https://instagram.com/odsc/'> <i class='fa fa-instagram instagram-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='https://bit.ly/35pfPZo'> <i class='fa fa-slack slack-awesome-social awesome-social'></i></a><br /><a target="_blank" class='fuse_social_icons_links' href='mailto:info@odsc.com'> <i class='fa fa-envelope envelope-awesome-social awesome-social'></i></a><br /> <div id="cookie-notice" role="dialog" class="cookie-notice-hidden cookie-revoke-hidden cn-position-bottom" aria-label="Cookie Notice" style="background-color: rgba(50,50,58,1);"><div class="cookie-notice-container" style="color: #fff"><span id="cn-notice-text" class="cn-text-container">We use cookies to ensure that we give you the best experience on our website. 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