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From build...@apache.org
Subject svn commit: r947317 - in /websites/staging/mahout/trunk/content: ./ index.html
Date Sun, 12 Apr 2015 17:12:29 GMT
Author: buildbot
Date: Sun Apr 12 17:12:29 2015
New Revision: 947317

Log:
Staging update by buildbot for mahout

Modified:
    websites/staging/mahout/trunk/content/   (props changed)
    websites/staging/mahout/trunk/content/index.html

Propchange: websites/staging/mahout/trunk/content/
------------------------------------------------------------------------------
--- cms:source-revision (original)
+++ cms:source-revision Sun Apr 12 17:12:29 2015
@@ -1 +1 @@
-1673030
+1673031

Modified: websites/staging/mahout/trunk/content/index.html
==============================================================================
--- websites/staging/mahout/trunk/content/index.html (original)
+++ websites/staging/mahout/trunk/content/index.html Sun Apr 12 17:12:29 2015
@@ -287,8 +287,19 @@
   </div>
   <p>The three major components of Mahout are an environment for building scalable
algorithms, many new Scala + Spark (H2O in progress) algorithms, and Mahout's mature Hadoop
MapReduce algorithms.</p>
   <h4><strong>11 Apr 2015 - Apache Mahout's next generation version 0.10.0 released</strong></h4>
-  <p><strong>Apache Mahout introduces a new math</strong> <a href="http://mahout.apache.org/users/sparkbindings/home.html"><strong>environment
we call Samsara</strong></a>, for its theme of universal renewal. It reflects
a fundamental rethinking of how scalable machine learning algorithms are built and customized.
Mahout-Samsara is here to help people create their own math while providing some off-the-shelf
algorithm implementations. At its base are general linear algebra and statistical operations
along with the data structures to support them. It’s written in Scala with Mahout-specific
extensions, and runs most fully on Spark.</p></p>
-<p><p><a href="http://mahout.apache.org/users/basics/algorithms.html"><strong>Mahout
Algorithms</strong></a> include many new implementations built for speed on Mahout-Samsara.
They run on Spark and some on H2o, which means as much as a 10x speed increase. You’ll
find robust matrix decomposition algorithms as well as a Naive Bayes classifier and collaborative
filtering.</p></p>
+  <p><strong>Apache Mahout introduces a new math environment we call</strong>
<a href="http://mahout.apache.org/users/sparkbindings/home.html"><strong>Samsara</strong></a>,

+    for its theme of universal renewal. It reflects a fundamental rethinking of how scalable
machine learning 
+    algorithms are built and customized. Mahout-Samsara is here to help people create their
own math while providing
+    some off-the-shelf algorithm implementations. At its base are general linear algebra
and statistical operations 
+   along with the data structures to support them. It’s written in Scala with Mahout-specific
extensions that look something like R, 
+   and runs most fully on Spark. Mahout-Samsara comes with an interactive shell that runs
distributed operations on a Spark cluster. 
+   This make prototyping or task submission much easier than before and allows users to customize
algorithms with
+   a whole ne degree of freedom.</p></p>
+<p><p><a href="http://mahout.apache.org/users/basics/algorithms.html"><strong>Mahout
Algorithms</strong></a> include many new 
+    implementations built for speed on Mahout-Samsara. They run on Spark and some on H2O,
which means as 
+    much as a 10x speed increase. You’ll find robust matrix decomposition algorithms
as well as a <strong><a href="http://mahout.apache.org/users/algorithms/spark-naive-bayes.html">Naive
Bayes</a></strong> 
+   classifier and collaborative filtering. The new spark-itemsimilarity enables the next
generation of <strong><a href="http://mahout.apache.org/users/algorithms/intro-cooccurrence-spark.html">cooccurrence

+   recommenders</a></strong> that can use entire user click streams and context
in making recommendations.</p></p>
 <p><p>Interested in helping? Join the <a href="https://mahout.apache.org/general/mailing-lists,-irc-and-archives.html">Mailing
lists</a>.</p></p>
 <h1 id="mahout-news">Mahout News</h1>
 <h4 id="1-february-2014-apache-mahout-09-released">1 February 2014 - Apache Mahout
0.9 released</h4>



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