Author: apalumbo
Date: Sat Apr 11 22:57:28 2015
New Revision: 1672943
URL: http://svn.apache.org/r1672943
Log:
remove the 'currently mahout is...' section try to fix Date header
Modified:
mahout/site/mahout_cms/trunk/content/index.mdtext
Modified: mahout/site/mahout_cms/trunk/content/index.mdtext
URL:
http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/index.mdtext?rev=1672943&r1=1672942&r2=1672943&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/index.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/index.mdtext Sat Apr 11 22:57:28 2015
@@ -26,7 +26,7 @@
</ul>
</div>
<p>The three major components of Mahout are an environment for building
scalable algorithms, many new Scala + Spark (H2O in progress) algorithms, and
Mahouts mature Hadoop MapReduce algorithms.</p>
- <p><h5> **11 Apr 2015 - Apache Mahout's next generation version 0.1.10
released**</h5></p>
+ <p>**11 Apr 2015 - Apache Mahout's next generation version 0.1.10
released**</h5>
<p>**Apache Mahout would like to introduce a new math** [**environment we
call Samsara**](http://mahout.apache.org/users/sparkbindings/home.html); for
its symbol 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>[**Mahout
Algorithms**](http://mahout.apache.org/users/basics/algorithms.html) include
many new implementations built for speed on Mahout-Samsara. They run on Spark
and some on H2o, which means as much as 10x speed increase. Youâll find
robust matrix decomposition algorithms as well as a Naive Bayes classifier and
collaborative filtering.</p>
@@ -40,11 +40,6 @@
<p>**Scalable community**. The goal of Mahout is to build a vibrant,
responsive, diverse community to facilitate
discussions not only on the project itself but also on potential use
cases. Come to the mailing lists to find out
more.</p>
- <p>Currently Mahout supports mainly three use cases: Recommendation mining
takes users' behavior and from that tries to
- find items users might like. Clustering takes e.g. text documents and
groups them into groups of topically related
- documents. Classification learns from exisiting categorized documents what
documents of a specific category look
- like and is able to assign unlabelled documents to the (hopefully) correct
category.</p>
-
<p>Interested in helping? Join the <a
href="https://mahout.apache.org/general/mailing-lists,-irc-and-archives.html";>Mailing
lists</a>.</p>
# Mahout News
