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. Itâs 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. Youâll 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. Itâs 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. Youâll 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>
