svn commit: r1672956 - /mahout/site/mahout_cms/trunk/content/index.mdtext

[apalumbo]

Author: apalumbo
Date: Sun Apr 12 00:59:20 2015
New Revision: 1672956

URL: http://svn.apache.org/r1672956
Log:
some cleanup

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=1672956&r1=1672955&r2=1672956&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/index.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/index.mdtext Sun Apr 12 00:59:20 2015
@@ -3,7 +3,7 @@
 </h2>
   <div class="highlights">
     <a href="http://mahout.apache.org/general/downloads.html";><img 
src="http://mahout.apache.org/images/download-mahout.png"/></a>
-    <h4>Latest release version 0.10.0 has</h4>
+    <h4>Latest release version 0.10.0 has:</h4>
     <h6>Mahout Samsara Environment</h3>
     <ul>
       <li>Spark and H2O back end Bindings</li>
@@ -17,9 +17,9 @@
     </ul>
     <h6>Mahout Samsara based Algorithms</h6>
     <ul>
-      <li>Distributed and in-core: Stochastic Singular Value Decomposition 
(SSVD)</li>
+      <li>Distributed and in-core Stochastic Singular Value Decomposition 
(SSVD)</li>
       <li>Distributed Principal Component Analysis (PCA)</li>
-      <li>Distributed Cholesky QR Reduction (QR)</li>
+      <li>Distributed and in-core QR Reduction (QR)</li>
       <li>Distributed Alternating Least Squares (ALS) method</li>
       <li>Collaborative Filtering: Item and Row Similarity based on 
co-occurrence and supporting multimodal user actions</li>
       <li>Naive Bayes Classification</li>
@@ -29,12 +29,12 @@
   <h4>**11 Apr 2015 - Apache Mahout's next generation version 0.10.0 
released**</h4>
   <p>**Apache Mahout introduces a new math** [**environment we call 
Samsara**](http://mahout.apache.org/users/sparkbindings/home.html), 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>[**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 a 10x speed increase. You’ll find 
robust matrix decomposition algorithms as well as a Naive Bayes classifier and 
collaborative filtering.</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 a 10x speed increase. You’ll find 
robust matrix decomposition algorithms as well as a Naive Bayes classifier and 
collaborative filtering.</p>
 
   <p>**Mahout MapReduce** includes the best of Hadoop MapReduce algorithms 
from Mahout v 0.9 but now with dependency updates and full Hadoop 2 support.</p>
 
   <h4>By scalable we mean:</h4>
-  <p>**Scalable to large data sets**. Our [core 
algorithms](http://mahout.apache.org/users/basics/algorithms.html) for 
clustering, classfication and collaborative filtering are implemented on top of 
scalable, distributed systems. However, contributions that run on a single 
machine are welcome as well.</p>
+  <p>**Scalable to large data sets**. Our [core 
algorithms](http://mahout.apache.org/users/basics/algorithms.html) for 
clustering, classfication and collaborative filtering are implemented on top of 
scalable, distributed systems.</p>
   <p>**Scalable to support your business case**. Mahout is distributed under a 
commercially friendly Apache Software
     license.</p>
   <p>**Scalable community**. The goal of Mahout is to build a vibrant, 
responsive, diverse community to facilitate