H2O description updated:

- text changed
- link changed to h2o-dev (the newest version of implementation)
- github link corrected to use h2oai account

Author: mmalohlava

index.html

@@ -635,16 +635,18 @@ <h2 id="project_tagline">This page is a summary to keep the track of Hadoop rela
 
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 <td width="20%">H2O</td>
-<td>H2O is a statistical, machine learning and math runtime tool for bigdata analysis. Developed by
-    the predictive analytics company 0xdata, H2O has established a leadership in the ML scene together
-    with R, Mahout and MLlib from Spark. According with 0xdata, H2O is the world’s fastest in-memory platform for 
-    machine learning and predictive analytics on big data, designed to help users scale machine learning, 
-    math, and statistics over large datasets. The tool can read and write from/to HDFS, S3, NoSQL, SQL,
-    load data from Excel CSV format from the local file system. It uses a JDBC driver for SQL and adapters
-    for NoSQL integration (in development righ now). The tool can be explotated with JSON and R-like language, and
-    is available a friendly user interface (GUI). The library is included as a regular tool in the Hortonworks and
-    Cloudera portfolio for in real-time better ML predictions.</td>
-<td width="20%"><a href="https://github.com/0xdata/h2o">1. H2O at GitHub</a></td>
+<td><p>H2O is a statistical, machine learning and math runtime tool for bigdata analysis.
+    Developed by the predictive analytics company H2O.ai, H2O has established a leadership
+    in the ML scene together with R and Databricks’ Spark. According to the team, 
+    H2O is the world’s fastest in-memory platform for machine learning and predictive analytics
+    on big data. It is designed to help users scale machine learning, math, and statistics over large datasets.</p>
+    <p>In addition to H2O’s point and click Web-UI, its REST API allows easy integration into various
+    clients. This means explorative analysis of data can be done in a typical fashion in R, Python, and Scala;
+    and entire workflows can be written up as automated scripts.</p>
+</td>
+<td width="20%"><a href="https://github.com/h2oai/h2o-dev">1. H2O at GitHub</a>
+<br/><a href="http://h2o.ai/blog">2. H2O Blog</a>
+</td>
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