Predictive Analytics and Forecasting Solutions

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' onclick='NVIDIAGDC.button.click(this, $(this).data("href"),true, function() { ;return NVIDIAGDC.button.callbacks(this); }); return false;'><div class='btn'><strong>WATCH VIDEO <span style="color: #76B900;" class="legal">(02:03) </span><span class="fas fa-angle-right fa-fw"></span></strong></div></a> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-12 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance00fc75ee_ddd9_41b7_a0d9_c6aaeaadcde4"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-0 mob-p-b-0 "> <div class="text-left lap-text-left tab-text-left mob-text-left"> <div class="description color-black body-text"><p>The growing practice of data science has made prediction and forecasting more common within enterprises, allowing businesses to leverage large-scale historical datasets to generate insights about the future. </p> <p>While predictive analytics is highly valuable, building effective, accurate models is an arduous process. Due to the data-intensive nature of prediction, data science teams often face computational bottlenecks and significant cycle time on CPU-based implementations. Through full-stack development, from software to hardware, NVIDIA provides accelerated solutions built upon popular data science solutions to solve common pain points and help businesses get the most out of their data.</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <script> NVIDIAGDC.funcQueue.addToQueue({ id : "columnlayoutenhanced6b10ec63_ce03_4776_8a13_425bb8c427f4", method : "columnlayoutenhanced", params : [{ columnsNumber: 2, imageBigDesktopUrl1: 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</div> </div> </div> </div> <div class="row no-divider equial-h-col" id="columnlayoutenhanced_1246837101747648e0_184a_435f_8897_2017fb09769d"> <div class="column small-12 medium-12 large-4 card2p"> <div class=""> </div> <div class="background-white card equi-height-col "> <div class="column-1 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance82c36a01_9302_444d_8981_f537c67b5a97"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-60 p-b-60 lap-p-t-45 lap-p-b-45 tab-p-t-30 tab-p-b-30 mob-p-t-30 mob-p-b-30 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h3 class="title color-brand-green no-space h4 none" >It’s Time Consuming</h3> <div class="description color-black body-text"><p><br> Creating accurate predictions requires a lot of data. 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Large-scale CPU infrastructure incurs significant costs, reducing the return on investment for data-driven enterprises.</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column small-12 medium-12 large-4 card2p"> <div class=""> </div> <div class="background-white card equi-height-col "> <div class="column-3 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance4f09ac64_d1e2_4faa_b282_cb3797d9c179"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-60 p-b-60 lap-p-t-45 lap-p-b-45 tab-p-t-30 tab-p-b-30 mob-p-t-30 mob-p-b-30 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h3 class="title color-brand-green no-space h4 none" >It’s Frustrating</h3> <div class="description color-black body-text"><p><br> Productionizing a large-scale prediction process is arduous. 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By developing software and hardware holistically, NVIDIA offers enterprise-grade solutions that make it easy for businesses to generate insights and deploy models to improve operations or better serve customers. With RAPIDS<sup>™</sup> and <a href="https://developer.nvidia.com/cuda-zone" target="_blank" rel="noopener noreferrer">CUDA</a><sup>®</sup>, data scientists can accelerate prediction and forecasting pipelines on NVIDIA GPUs, reducing operations like data loading, processing, and training from days to minutes. NVIDIA accelerated computation can be harnessed through familiar Python- or Java-based languages, making it simple to get started with accelerated data science. Global NVIDIA Enterprise Support is available with <a href="https://www.nvidia.com/en-us/data-center/products/ai-enterprise/">NVIDIA AI Enterprise</a>, an end-to-end AI software suite, and includes guaranteed response times, priority security notifications, regular updates, and access to NVIDIA AI experts.</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </section> <script type="text/javascript"> NVIDIAGDC.funcQueue.addToQueue({ id : "sectionenhanced_697697562949603a0_d0ee_4742_af4d_95fd588d28b1", method : "sectionEnhancedComponent", params : [{ imageDesktopUrl:' ', imageLaptopUrl:' ', imageTabletUrl:' ', imageMobileUrl:' ', secpageobpvalue: 'false', sectionurl: '', sectionurltarget: '_self', secCustBgColor:'' }] }); </script>   </div> <div class="sectionenhanced parbase section"> <section class=" background-body-copy p-t-30 p-b-30 lap-p-t-30 lap-p-b-30 tab-p-t-30 tab-p-b-30 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Integrations with leading data science frameworks like Apache Spark, cuPY, Dask, XGBoost, and Numba, as well as numerous deep learning frameworks such as PyTorch, TensorFlow, and Apache MxNet, broaden adoption and encourage further integration across the data science ecosystem. 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<div class="text-right lap-text-right tab-text-right mob-text-right"> <div class="description color-brand-green body-text"><p> </p> <p><span style="font-size: 54.0px;">100X<br>  </span></p> <p><span style="font-size: 54.0px;">20X</span></p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-6 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance18f03285_822b_4fcb_92f4_7444cc8ae381"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-45 mob-p-b-0 "> <div class="text-left lap-text-left tab-text-left mob-text-left"> <div class="description color-brand-green body-text"><h4>Faster<br> feature engineering<p><br> <br> Faster<br> model training</p> </h4></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <script> NVIDIAGDC.funcQueue.addToQueue({ id : "columnlayoutenhanced_955936051ab67a03c_2370_48ba_b08f_2f227b8a87b5", method : "columnlayoutenhanced", params : [{ columnsNumber: 2, imageBigDesktopUrl1: 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mobNoResponsive:"true", tabNoResponsive:"", tabSingleCol:"", }] }); </script> </div> </div> </div>   </div> <div class="textcomponentenhanced section"> <div id="textcomponentenhance1a6aecd0_c5e8_4df7_9de8_bb3c02aa443c"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-15 p-b-0 lap-p-t-15 lap-p-b-0 tab-p-t-15 tab-p-b-0 mob-p-t-15 mob-p-b-0 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h3 class="title color-brand-green h3 none" >Millions of dollars saved by improving forecasting processes</h3> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <script> NVIDIAGDC.funcQueue.addToQueue({ id : "columnlayoutenhanced_798352139bab8008d_2d39_4bc9_b6dc_7645a33b63bc", method : "columnlayoutenhanced", params : [{ columnsNumber: 2, imageBigDesktopUrl1: 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class="text-right lap-text-right tab-text-right mob-text-right"> <div class="description color-brand-green body-text"><p> </p> <p><span style="font-size: 54.0px;">100X<br>  </span></p> <p><span style="font-size: 54.0px;">97%</span></p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-6 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhance42428b44_c30b_4dc4_9521_59e6804bb134"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-0 p-b-0 lap-p-t-0 lap-p-b-0 tab-p-t-0 tab-p-b-0 mob-p-t-45 mob-p-b-0 "> <div class="text-left lap-text-left tab-text-left mob-text-left"> <div class="description color-brand-green 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To better serve their customers, Capital One has undergone a significant transformation, turning from a bank that uses technology to a technology company that does banking.</p> <p>As part of that transformation, Capital One has leaned into data science. To power a data-driven culture, Capital One has adopted <a href="https://www.capitalone.com/tech/machine-learning/dask-and-rapids-data-science-and-machine-learning-at-capital-one/">RAPIDS, Dask, and NVIDIA GPUs</a>, substantially improving performance and return on investment for their prediction operations. Powered by NVIDIA accelerated data science, Capital One has the tools they need to truly “change banking for good.”</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"><div class="button parbase section"> <div class="text-left lap-text-left tab-text-left mob-text-left p-t-30 p-b-30 lap-p-t-30 lap-p-b-30 tab-p-t-30 tab-p-b-30 mob-p-t-30 mob-p-b-0 mobile-align "> <div class="noicon " > <a href='https://developer.nvidia.com/gtc/2020/video/s22136-vid' data-analytics="txt-manual:" data-title="" data-href='https://developer.nvidia.com/gtc/2020/video/s22136-vid' rel="noopener noreferrer" target="_blank" class=' link-txt txt-manual brand-green regular-btn ' onclick='NVIDIAGDC.button.click(this, $(this).data("href"),true, function() { ;return NVIDIAGDC.button.callbacks(this); }); return false;'><div class='btn'><span class="far fa-play-circle fa-fw"></span><b>Watch GTC2020 Session: Scaling PyData with Dask and RAPIDS at Capital One </b><span class="legal">(17:47 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To better serve their customers, Capital One has undergone a significant transformation, turning from a bank that uses technology to a technology company that does banking.</p> <p>As part of that transformation, Capital One has leaned into data science. To power a data-driven culture, Capital One has adopted <a href="https://www.capitalone.com/tech/machine-learning/dask-and-rapids-data-science-and-machine-learning-at-capital-one/">RAPIDS, Dask, and NVIDIA GPUs</a>, substantially improving performance and return on investment for their prediction operations. Powered by NVIDIA accelerated data science, Capital One has the tools they need to truly “change banking for good.”</p></div> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"><div class="button parbase section"> <div class="text-left lap-text-left tab-text-left mob-text-left p-t-30 p-b-30 lap-p-t-30 lap-p-b-30 tab-p-t-30 tab-p-b-30 mob-p-t-30 mob-p-b-30 mobile-align "> <div class="noicon " > <a href='https://developer.nvidia.com/gtc/2020/video/s22136-vid' data-analytics="txt-manual:" data-title="" data-href='https://developer.nvidia.com/gtc/2020/video/s22136-vid' rel="noopener noreferrer" target="_blank" class=' link-txt txt-manual brand-green regular-btn ' onclick='NVIDIAGDC.button.click(this, $(this).data("href"),true, function() { ;return NVIDIAGDC.button.callbacks(this); }); return false;'><div class='btn'><span class="far fa-play-circle fa-fw"></span><b>Watch GTC2020 Session: Scaling PyData with Dask and RAPIDS at Capital One </b><span class="legal">(17:47 Minutes)</span></div></a> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> <div class="column right-column small-12 medium-12 large-6 order-1 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-2 parsys"><div class="columnLayoutEnhanced parbase section"> <div class="background-white p-t-30 p-b-0 lap-p-t-30 lap-p-b-0 tab-p-t-30 tab-p-b-0 mob-p-t-30 mob-p-b-0 hide-mob " > <div class="column-container clearfix "> <div class="large-12 large-12 medium-12 small-12 center"> <div class="row no-divider equial-h-col" id="columnlayoutenhanced96177f37_affa_40b0_8b10_babcb535beec"> <div class="column left-column small-12 medium-6 large-6 "> <div class=""></div> <div class="background-none equi-height-col "> <div class="column-1 parsys"><div class="textcomponentenhanced section"> <div id="textcomponentenhancee49e20ca_aeff_486d_bef9_6da58dd3e8c0"> <div class="general-container-text 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mobNoResponsive:"", tabNoResponsive:"", tabSingleCol:"", }] }); </script> </div> </div> </div>   </div> <div class="textcomponentenhanced section"> <div id="textcomponentenhanceffde5b0e_61b4_4f7d_8125_9823b09cce9e"> <div class="general-container-text small-12 mob-p-content medium-12 tab-p-content large-12 lap-p-content large-12 d-p-content p-t-15 p-b-0 lap-p-t-15 lap-p-b-0 tab-p-t-15 tab-p-b-0 mob-p-t-15 mob-p-b-0 "> <div class="text-center lap-text-center tab-text-center mob-text-center"> <h3 class="title color-brand-green h3 none" >Accurate results for less money to better serve customers</h3> <div class="text-button"> <div class="textCmpEnhancedButton-par parsys"> </div> </div> </div> </div> </div> </div> </div> </div> <div class="singlecolumnborder"></div> </div> </div> <script> NVIDIAGDC.funcQueue.addToQueue({ id : "columnlayoutenhanced_13158566460d976888_35f1_4446_8bd0_891a10af85bd", method : "columnlayoutenhanced", params : [{ columnsNumber: 2, imageBigDesktopUrl1: 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