svn commit: r1672943 - /mahout/site/mahout_cms/trunk/content/index.mdtext

[ap...@apache.org]

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. It’s 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. You’ll 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