Author: akm
Date: Sat Apr 11 23:30:40 2015
New Revision: 1672944
URL: http://svn.apache.org/r1672944
Log:
Fixing typos on the home page for the 0.10.0 announcement
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=1672944&r1=1672943&r2=1672944&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/index.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/index.mdtext Sat Apr 11 23:30:40 2015
@@ -25,15 +25,15 @@
<li>Naive Bayes Classification</li>
</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>**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>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>
+ <h5>**11 Apr 2015 - Apache Mahout's next generation version 0.10.0
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 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>[**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>
+ <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. Youâll 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>
- <p>With scalable we mean:</p>
+ <h5>By scalable we mean:</h5>
<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 support your business case**. Mahout is distributed under a
commercially friendly Apache Software
license.</p>
