Updated to Oryx 2.0

README.md

@@ -269,7 +269,7 @@ For a list of free machine learning books available for download, go [here](http
 * [Meka](http://meka.sourceforge.net/) - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
 * [MLlib in Apache Spark](http://spark.apache.org/docs/latest/mllib-guide.html) - Distributed machine learning library in Spark
 * [Neuroph](http://neuroph.sourceforge.net/) - Neuroph is lightweight Java neural network framework
-* [ORYX](https://github.com/cloudera/oryx) - Simple real-time large-scale machine learning infrastructure.
+* [ORYX](https://github.com/oryxproject/oryx) - Lambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.
 * [RankLib](http://sourceforge.net/p/lemur/wiki/RankLib/) - RankLib is a library of learning to rank algorithms
 * [RapidMiner](http://rapid-i.com/wiki/index.php?title=Integrating_RapidMiner_into_your_application) - RapidMiner integration into Java code
 * [Stanford Classifier](http://nlp.stanford.edu/software/classifier.shtml) - A classifier is a machine learning tool that will take data items and place them into one of k classes.