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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="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>
     &nbsp;			</div>
 	</div>

     <div class="container">
 		<div class="post">
 			<h2>MADlib 1.16 Release</h2>
 			On July 8, 2019, MADlib completed its sixth 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 - Early stage support for Keras with Tensorflow
     backend with GPU acceleration.  Focus on image classification
     use cases.</p>
     <li><p dir="ltr">Deep learning utilities - Load model architectures and
     weights, parallel loading of images from NumPy arrays
     or file system, preprocess images for gradient descent
     optimization algorithms.</p>
     <li><p dir="ltr">Greenplum 6 support.</p>
     <li><p dir="ltr">PostgreSQL 11 support.</p>
     </ul>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">K-nearest neighbors - Improve performance with kd-tree approximate method.</p>
     <li><p dir="ltr">Association rules - Set default maximum itemset rules to 10 to reduce runtime.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.16/">download the 1.16 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>
 	</div>

     <div class="container">
 		<div class="post">
 			<h2>MADlib 1.15.1 Release</h2>
 			On Oct 15, 2018, MADlib completed its fifth release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include</b>: Ubuntu 16.04 support.</p>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Elastic net - Support grouping by non-numeric columns.</p>
     <li><p dir="ltr">K-nearest neighbors - Accept expressions for points.</p>
     <li><p dir="ltr">Vec2cols - Allow arrays of different lengths.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.15.1/">download the 1.15.1 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
 	&nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.15 Release</h2>
 			On Aug 10, 2018, MADlib completed its fourth release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include</b>: Utilities - Columns to vector, vector to columns, drop columns.</p>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">Multilayer perceptron - Added momentum and Nesterov's accelerated gradient methods to gradient updates.</p>
     <li><p dir="ltr">Statistics - Added grouping support to correlation and covariance.</p>
     <li><p dir="ltr">Decision tree/random forest - Added impurity variable importance.</p>
     <li><p dir="ltr">Decision tree/random forest - Added new helper function to report variable importance values in a more readable way.</p>
     <li><p dir="ltr">Install - Refactored and updated the madpack installation and upgrade tool.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.15/">download the 1.15 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
 	&nbsp;			</div>
 	</div>

 	<div class="container">
 		<div class="post">
 			<h2>MADlib 1.14 Release</h2>
 			On May 1, 2018, MADlib completed its third release as an Apache Software Foundation Top Level Project.</a>
 	<p dir="ltr"></p>
     <p dir="ltr"><b>New features include</b>: Balanced datasets, personalized PageRank, mini-batch optimizer for multilayer perceptron neural networks (and associated pre-processor function), PostgreSQL 10.2 support.</p>
     <p dir="ltr"><b>Improvements:</b></p>
     <ul>
     <li><p dir="ltr">K-nearest neighbors - Added weighted averaging/voting by distance.</p>
     <li><p dir="ltr">Summary - Added more statistics including number of positive, negative, zero values and
     95% confidence intervals.</p>
     <li><p dir="ltr">Multilayer perceptron - Added support for one-hot encoded categorical dependent variable
     for classification.</p>
     </ul>
 	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.14/">download the 1.14 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
 	&nbsp;			</div>
 	</div>

     <div class="container">
 		<div class="post">
 			<h2>MADlib Graduates to Apache Top Level Project</h2>
 			On July 19, 2017, the ASF board established Apache MADlib as a Top Level Project, which was approved by unanimous vote of the directors present.  Please see the associated <a href="https://globenewswire.com/news-release/2017/08/22/1090924/0/en/The-Apache-Software-Foundation-Announces-Apache-MADlib-as-a-Top-Level-Project.html">press release from the ASF.</a>
 	<p dir="ltr"></p>
 	<p dir="ltr">MADlib entered incubation in the fall of 2015 and made five releases as an incubating project.  Along the way, the MADlib community has worked hard to ensure that the project is being developed according to the principles of the  <a href="http://apache.org/foundation/governance/">The Apache Way</a>.  We will continue to do so in the future as a TLP, to the best of our ability.</p>
 	<p dir="ltr">Thank you to all who have contributed to the project so far, and we look forward more innovation in machine learning in the future as a TLP!</a></p>
 	&nbsp;			</div>

 	<div class="resources">
 	<div class="container por">
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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>
 	</li>
 	</ul>
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 	      Copyright &copy; <script>	var d = new Date();document.write(d.getFullYear());</script> <a href='http://www.apache.org/'>The Apache Software Foundation</a>
 	      <br>
 	      Apache, Apache MADlib, the Apache feather and the MADlib logo are trademarks of The Apache Software Foundation
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	<div class="panel">
	<div class="container por">
	<div class="row">
	<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>

	</div>
	</div>
	</div>
	<div class="primary-content">
	<div class="container">
	<div class="row">
	<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 1.16 Release</h2>
	On July 8, 2019, MADlib completed its sixth 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 - Early stage support for Keras with Tensorflow
	backend with GPU acceleration. Focus on image classification
	use cases.</p>
	<li><p dir="ltr">Deep learning utilities - Load model architectures and
	weights, parallel loading of images from NumPy arrays
	or file system, preprocess images for gradient descent
	optimization algorithms.</p>
	<li><p dir="ltr">Greenplum 6 support.</p>
	<li><p dir="ltr">PostgreSQL 11 support.</p>
	</ul>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">K-nearest neighbors - Improve performance with kd-tree approximate method.</p>
	<li><p dir="ltr">Association rules - Set default maximum itemset rules to 10 to reduce runtime.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://dist.apache.org/repos/dist/release/madlib/1.16/">download the 1.16 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>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.15.1 Release</h2>
	On Oct 15, 2018, MADlib completed its fifth release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include</b>: Ubuntu 16.04 support.</p>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Elastic net - Support grouping by non-numeric columns.</p>
	<li><p dir="ltr">K-nearest neighbors - Accept expressions for points.</p>
	<li><p dir="ltr">Vec2cols - Allow arrays of different lengths.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.15.1/">download the 1.15.1 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.15 Release</h2>
	On Aug 10, 2018, MADlib completed its fourth release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include</b>: Utilities - Columns to vector, vector to columns, drop columns.</p>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">Multilayer perceptron - Added momentum and Nesterov's accelerated gradient methods to gradient updates.</p>
	<li><p dir="ltr">Statistics - Added grouping support to correlation and covariance.</p>
	<li><p dir="ltr">Decision tree/random forest - Added impurity variable importance.</p>
	<li><p dir="ltr">Decision tree/random forest - Added new helper function to report variable importance values in a more readable way.</p>
	<li><p dir="ltr">Install - Refactored and updated the madpack installation and upgrade tool.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.15/">download the 1.15 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib 1.14 Release</h2>
	On May 1, 2018, MADlib completed its third release as an Apache Software Foundation Top Level Project.</a>
	<p dir="ltr"></p>
	<p dir="ltr"><b>New features include</b>: Balanced datasets, personalized PageRank, mini-batch optimizer for multilayer perceptron neural networks (and associated pre-processor function), PostgreSQL 10.2 support.</p>
	<p dir="ltr"><b>Improvements:</b></p>
	<ul>
	<li><p dir="ltr">K-nearest neighbors - Added weighted averaging/voting by distance.</p>
	<li><p dir="ltr">Summary - Added more statistics including number of positive, negative, zero values and
	95% confidence intervals.</p>
	<li><p dir="ltr">Multilayer perceptron - Added support for one-hot encoded categorical dependent variable
	for classification.</p>
	</ul>
	<p dir="ltr">You are invited to <a href="https://archive.apache.org/dist/madlib/1.14/">download the 1.14 release</a> and <a href="https://github.com/apache/madlib/blob/master/RELEASE_NOTES">review the release notes.</a></p>
	</div>
	</div>

	<div class="container">
	<div class="post">
	<h2>MADlib Graduates to Apache Top Level Project</h2>
	On July 19, 2017, the ASF board established Apache MADlib as a Top Level Project, which was approved by unanimous vote of the directors present. Please see the associated <a href="https://globenewswire.com/news-release/2017/08/22/1090924/0/en/The-Apache-Software-Foundation-Announces-Apache-MADlib-as-a-Top-Level-Project.html">press release from the ASF.</a>
	<p dir="ltr"></p>
	<p dir="ltr">MADlib entered incubation in the fall of 2015 and made five releases as an incubating project. Along the way, the MADlib community has worked hard to ensure that the project is being developed according to the principles of the <a href="http://apache.org/foundation/governance/">The Apache Way</a>. We will continue to do so in the future as a TLP, to the best of our ability.</p>
	<p dir="ltr">Thank you to all who have contributed to the project so far, and we look forward more innovation in machine learning in the future as a TLP!</a></p>
	</div>

	<div class="resources">
	<div class="container por">
	<div class="row">
	<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>
	</li>
	</ul>
	</div>
	</div>
	</div>
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	Copyright © <script> var d = new Date();document.write(d.getFullYear());</script> <a href='http://www.apache.org/'>The Apache Software Foundation</a>
	<br>
	Apache, Apache MADlib, the Apache feather and the MADlib logo are trademarks of The Apache Software Foundation
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