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 	<h2 style="margin: 35px 0 15px 110px;">Apache MADlib: Big Data Machine Learning in SQL</h2>
 	<ul class="intro-text">
 		<li class="offset1 span3">Open source, commercially friendly Apache license</li>
 		<li class="span3">For PostgreSQL and Greenplum Database<sup>&reg;</sup></li>
 		<li class="span3">Powerful machine learning, graph, statistics and analytics for data scientists</li>
 	</ul>
 	<p class="more"><a class="large-link pointer point-right" href="product.html">Read More</a></p>

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 		<div class="post">
 			<h2>Getting Started with Apache MADlib using Jupyter Notebooks</h2>
 			We have created a <a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts">library of Jupyter Notebooks</a> to help you get started quickly with MADlib.  It
 			includes many commonly used algorithms by data scientists.</a>
 	<p dir="ltr"></p>
     &nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.21.0 Release</h2>
 			On March 1, 2023, MADlib completed its eleventh release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include:</b></p>
     <ul>
     <li><p dir="ltr">Graph: Add warm start for weakly connected components.</p>
     <li><p dir="ltr">Graph: Add multicolumn identifier support for SSSP and APSP.</p>
     <li><p dir="ltr">Build: Add support for Photon3 OS.</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">XGBoost: Add support for bigint and varchar columns.</p>
     <li><p dir="ltr">XGBoost: Enable eval_metrics parameter.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.21.0/">download the 1.21.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
 	&nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.20.0 Release</h2>
 			On August 3, 2022, MADlib completed its tenth release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include:</b></p>
     <ul>
     <li><p dir="ltr">XGBoost: Python based XGBoost with single and grid search executions.</p>
     <li><p dir="ltr">Graph: Add multicolumn support for WCC and Pagerank.</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Utilities: Reuse update plan in GroupIterationController.</p>
     <li><p dir="ltr">Documentation: Update online examples for various modules.</p>
     <li><p dir="ltr">Elastic Net - GLM - SVM: Adjust ORCA to reduce planning time.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.20.0/">download the 1.20.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
 	&nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.19.0 Release</h2>
 			On March 8, 2022, MADlib completed its ninth release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include:</b></p>
     <ul>
     <li><p dir="ltr">DBSCAN: Fast parallel-optimized DBSCAN.</p>
     <li><p dir="ltr">MLP: Add rmsprop and Adam optimization techniques.</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Graph: Improve WCC subtx count and catalog entry frequency.</p>
     <li><p dir="ltr">MLP: Set lambda value for minibatch.</p>
     <li><p dir="ltr">GLM-multinom: Use non-temp tables in GroupIterationController.</p>
     <li><p dir="ltr">Jenkins: Add new dockerfile for PG11.</p>
     <li><p dir="ltr">Build: Use dynamic_library_path for module pathname.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.19.0/">download the 1.19.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
 	&nbsp;			</div>
 	</div>

     <div class="container">
 		<div class="post">
 			<h2>MADlib 1.18.0 Release</h2>
 			On April 5, 2021, MADlib completed its eighth release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include:</b></p>
     <ul>
     <li><p dir="ltr">Deep learning - New grid and random search methods.</p>
     <li><p dir="ltr">Deep learning - AutoML methods Hyperband and Hyperopt.</p>
     <li><p dir="ltr">Deep learning - Custom loss functions and custom metrics.</p>
     <li><p dir="ltr">Deep learning - TensorBoard support.</p>
     <li><p dir="ltr">Deep learning - Multi-input and output support for fit and evaluate.</p>
     <li><p dir="ltr">DBSCAN - Density based clustering (phase 1).</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Deep learning - Implement cache logic to speed performance.</p>
     <li><p dir="ltr">Deep learning - Reduce GPU idle time when moving model state between workers.</p>
     <li><p dir="ltr">Deep learning - Use Keras version from TensorFlow.</p>
     <li><p dir="ltr">Deep learning - Add top n to evaluate.</p>
     <li><p dir="ltr">Graph - Support BIGINT for all graph methods.</p>
     <li><p dir="ltr">Infra - Switch to CloudBees (was Jenkins).</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.18.0/">download the 1.18.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
 	&nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.17.0 Release</h2>
 			On April 9, 2020, MADlib completed its seventh release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include:</b></p>
     <ul>
     <li><p dir="ltr">Deep learning - Model selection framework for
     Keras with Tensorflow
     backend with GPU acceleration, for model architecture search and
     hyperparameter optimization.</p>
     <li><p dir="ltr">Deep learning - Support for heterogeneous clusters
     where GPUs are attached to only certain segment hosts.</p>
     <li><p dir="ltr">Deep learning - Support inference for imported
     models not trained in MADlib ("bring your own model").</p>
     <li><p dir="ltr">Deep learning - Support transfer learning
     for multiple model fit function.</p>
     <li><p dir="ltr">Deep learning - Generate model selection
     table for grid search or random search.</p>
     <li><p dir="ltr">Deep learning - Helper function to
     get GPU type and configuration in a database cluster.</p>
     <li><p dir="ltr">k-Means clustering - Select optimal number of centroids
     using elbow or silhouette methods.</p>
     <li><p dir="ltr">PostgreSQL 12 support.</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Association rules - Add option to set number
     of posterior rules.</p>
     <li><p dir="ltr">Correlation and covariance - Improve memory
     usage with large number of groups.</p>
     <li><p dir="ltr">Deep learning - Improve performance of
     mini-batch preprocessor and fit functions.</p>
     <li><p dir="ltr">Docs - Inprove installation guide on wiki.</p>
     <li><p dir="ltr">Graph - SSSP should not show vertices in output
     table that are unreachable.</p>
     <li><p dir="ltr">LDA - Add stopping criteria on perplexity.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.17.0/">download the 1.17.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a>
 	For more details about the new deep learning feature, please refer to the
 	<a href="https://cwiki.apache.org/confluence/display/MADLIB/Deep+Learning">Apache MADlib deep learning notes</a> and
 	the <a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts/Deep-learning">Jupyter notebook examples.</a></p>
 	&nbsp;			</div>
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 	<h2><small>Downloads</small></h2>
 	<p><a href="download.html">Downloads for Apache MADlib releases.</a> This also includes links to pre-Apache MADlib releases.
 		<li class="span4">
 	<h2><small>Documentation</small></h2>
 	<ul>
 		<li><a href="docs/latest/index.html">User Guide</a></li>
 		<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/">MADlib Wiki</a></li>
 		<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Installation+Guide">Installation Guide</a></li>
 		<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Users">Quick Start Guide for Users</a></li>
 		<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers">Quick Start Guide for Developers</a></li>

 	</ul>
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 		<li class="span4">
 	<h2><small>Additional Resources</small></h2>
 	<ul>
 		<li><a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts">Getting Started with MADlib - Jupyter Notebooks</a></li>
 		<li><a href="https://www.youtube.com/channel/UCIC2TGO-4xNSAJFCJXlJNwA">Greenplum Database YouTube Channel with MADlib Content</a></li>
 		<li><a href="community.html#contribution">Contribution Information</a></li>
 		<li><a href="community.html#research">Research Papers</a></li>
 		<li><a href="community.html#datasets">Datasets</a></li>
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	<h2 style="margin: 35px 0 15px 110px;">Apache MADlib: Big Data Machine Learning in SQL</h2>
	<ul class="intro-text">
	<li class="offset1 span3">Open source, commercially friendly Apache license</li>
	<li class="span3">For PostgreSQL and Greenplum Database<sup>®</sup></li>
	<li class="span3">Powerful machine learning, graph, statistics and analytics for data scientists</li>
	</ul>
	<p class="more"><a class="large-link pointer point-right" href="product.html">Read More</a></p>

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	<div class="span8 news-posts por">

	<div class="container">
	<div class="post">
	<h2>Getting Started with Apache MADlib using Jupyter Notebooks</h2>
	We have created a <a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts">library of Jupyter Notebooks</a> to help you get started quickly with MADlib. It
	includes many commonly used algorithms by data scientists.</a>
	<p dir="ltr"></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.21.0 Release</h2>
	On March 1, 2023, MADlib completed its eleventh release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include:</b></p>
	<ul>
	<li><p dir="ltr">Graph: Add warm start for weakly connected components.</p>
	<li><p dir="ltr">Graph: Add multicolumn identifier support for SSSP and APSP.</p>
	<li><p dir="ltr">Build: Add support for Photon3 OS.</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">XGBoost: Add support for bigint and varchar columns.</p>
	<li><p dir="ltr">XGBoost: Enable eval_metrics parameter.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.21.0/">download the 1.21.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.20.0 Release</h2>
	On August 3, 2022, MADlib completed its tenth release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include:</b></p>
	<ul>
	<li><p dir="ltr">XGBoost: Python based XGBoost with single and grid search executions.</p>
	<li><p dir="ltr">Graph: Add multicolumn support for WCC and Pagerank.</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Utilities: Reuse update plan in GroupIterationController.</p>
	<li><p dir="ltr">Documentation: Update online examples for various modules.</p>
	<li><p dir="ltr">Elastic Net - GLM - SVM: Adjust ORCA to reduce planning time.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.20.0/">download the 1.20.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.19.0 Release</h2>
	On March 8, 2022, MADlib completed its ninth release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include:</b></p>
	<ul>
	<li><p dir="ltr">DBSCAN: Fast parallel-optimized DBSCAN.</p>
	<li><p dir="ltr">MLP: Add rmsprop and Adam optimization techniques.</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Graph: Improve WCC subtx count and catalog entry frequency.</p>
	<li><p dir="ltr">MLP: Set lambda value for minibatch.</p>
	<li><p dir="ltr">GLM-multinom: Use non-temp tables in GroupIterationController.</p>
	<li><p dir="ltr">Jenkins: Add new dockerfile for PG11.</p>
	<li><p dir="ltr">Build: Use dynamic_library_path for module pathname.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.19.0/">download the 1.19.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.18.0 Release</h2>
	On April 5, 2021, MADlib completed its eighth release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include:</b></p>
	<ul>
	<li><p dir="ltr">Deep learning - New grid and random search methods.</p>
	<li><p dir="ltr">Deep learning - AutoML methods Hyperband and Hyperopt.</p>
	<li><p dir="ltr">Deep learning - Custom loss functions and custom metrics.</p>
	<li><p dir="ltr">Deep learning - TensorBoard support.</p>
	<li><p dir="ltr">Deep learning - Multi-input and output support for fit and evaluate.</p>
	<li><p dir="ltr">DBSCAN - Density based clustering (phase 1).</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Deep learning - Implement cache logic to speed performance.</p>
	<li><p dir="ltr">Deep learning - Reduce GPU idle time when moving model state between workers.</p>
	<li><p dir="ltr">Deep learning - Use Keras version from TensorFlow.</p>
	<li><p dir="ltr">Deep learning - Add top n to evaluate.</p>
	<li><p dir="ltr">Graph - Support BIGINT for all graph methods.</p>
	<li><p dir="ltr">Infra - Switch to CloudBees (was Jenkins).</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.18.0/">download the 1.18.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a> Also please refer to the <a href="https://cwiki.apache.org/confluence/display/MADLIB/Database+and+OS+Support">list of supported databases and OS.</a></p>
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	<div class="container">
	<div class="post">
	<h2>MADlib 1.17.0 Release</h2>
	On April 9, 2020, MADlib completed its seventh release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include:</b></p>
	<ul>
	<li><p dir="ltr">Deep learning - Model selection framework for
	Keras with Tensorflow
	backend with GPU acceleration, for model architecture search and
	hyperparameter optimization.</p>
	<li><p dir="ltr">Deep learning - Support for heterogeneous clusters
	where GPUs are attached to only certain segment hosts.</p>
	<li><p dir="ltr">Deep learning - Support inference for imported
	models not trained in MADlib ("bring your own model").</p>
	<li><p dir="ltr">Deep learning - Support transfer learning
	for multiple model fit function.</p>
	<li><p dir="ltr">Deep learning - Generate model selection
	table for grid search or random search.</p>
	<li><p dir="ltr">Deep learning - Helper function to
	get GPU type and configuration in a database cluster.</p>
	<li><p dir="ltr">k-Means clustering - Select optimal number of centroids
	using elbow or silhouette methods.</p>
	<li><p dir="ltr">PostgreSQL 12 support.</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Association rules - Add option to set number
	of posterior rules.</p>
	<li><p dir="ltr">Correlation and covariance - Improve memory
	usage with large number of groups.</p>
	<li><p dir="ltr">Deep learning - Improve performance of
	mini-batch preprocessor and fit functions.</p>
	<li><p dir="ltr">Docs - Inprove installation guide on wiki.</p>
	<li><p dir="ltr">Graph - SSSP should not show vertices in output
	table that are unreachable.</p>
	<li><p dir="ltr">LDA - Add stopping criteria on perplexity.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.17.0/">download the 1.17.0 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a>
	For more details about the new deep learning feature, please refer to the
	<a href="https://cwiki.apache.org/confluence/display/MADLIB/Deep+Learning">Apache MADlib deep learning notes</a> and
	the <a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts/Deep-learning">Jupyter notebook examples.</a></p>
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	<ul class="list-unstyled">
	<li class="span4">
	<h2><small>Downloads</small></h2>
	<p><a href="download.html">Downloads for Apache MADlib releases.</a> This also includes links to pre-Apache MADlib releases.
	<li class="span4">
	<h2><small>Documentation</small></h2>
	<ul>
	<li><a href="docs/latest/index.html">User Guide</a></li>
	<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/">MADlib Wiki</a></li>
	<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Installation+Guide">Installation Guide</a></li>
	<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Users">Quick Start Guide for Users</a></li>
	<li><a href="https://cwiki.apache.org/confluence/display/MADLIB/Quick+Start+Guide+for+Developers">Quick Start Guide for Developers</a></li>

	</ul>
	</li>
	<li class="span4">
	<h2><small>Additional Resources</small></h2>
	<ul>
	<li><a href="https://github.com/apache/madlib-site/tree/asf-site/community-artifacts">Getting Started with MADlib - Jupyter Notebooks</a></li>
	<li><a href="https://www.youtube.com/channel/UCIC2TGO-4xNSAJFCJXlJNwA">Greenplum Database YouTube Channel with MADlib Content</a></li>
	<li><a href="community.html#contribution">Contribution Information</a></li>
	<li><a href="community.html#research">Research Papers</a></li>
	<li><a href="community.html#datasets">Datasets</a></li>
	</ul>
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	</ul>
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