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added three links and sorted the JAVA ML section 

added Java-ML, RapidMiner Java extension and RankLib
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Omri Mendels 2014-12-07 09:13:54 +02:00
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@ -243,20 +243,23 @@ For a list of free machine learning books available for download, go [here](http
<a name="java-general-purpose" />
#### General-Purpose Machine Learning
* [JSAT](https://code.google.com/p/java-statistical-analysis-tool/) - Numerous Machine Learning algoirhtms for classification, regresion, and clustering.
* [MLlib in Apache Spark](http://spark.apache.org/docs/latest/mllib-guide.html) - Distributed machine learning library in Spark
* [Datumbox](https://github.com/datumbox/datumbox-framework) - Machine Learning framework for rapid development of Machine Learning and Statistical applications
* [Mahout](https://github.com/apache/mahout) - Distributed machine learning
* [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.
* [Weka](http://www.cs.waikato.ac.nz/ml/weka/) - Weka is a collection of machine learning algorithms for data mining tasks
* [Meka](http://meka.sourceforge.net/) - An open source implementation of methods for multi-label classification and evaluation (extension to Weka).
* [ORYX](https://github.com/cloudera/oryx) - Simple real-time large-scale machine learning infrastructure.
* [H2O](https://github.com/0xdata/h2o) - ML engine that supports distributed learning on data stored in HDFS.
* [WalnutiQ](https://github.com/WalnutiQ/WalnutiQ) - object oriented model of the human brain
* [ELKI](http://elki.dbs.ifi.lmu.de/) - Java toolkit for data mining. (unsupervised: clustering, outlier detection etc.)
* [Neuroph](http://neuroph.sourceforge.net/) - Neuroph is lightweight Java neural network framework
* [java-deeplearning](https://github.com/agibsonccc/java-deeplearning) - Distributed Deep Learning Platform for Java, Clojure,Scala
* [H2O](https://github.com/0xdata/h2o) - ML engine that supports distributed learning on data stored in HDFS.
* [htm.java](https://github.com/numenta/htm.java) - General Machine Learning library using Numenta’s Cortical Learning Algorithm
* [java-deeplearning](https://github.com/agibsonccc/java-deeplearning) - Distributed Deep Learning Platform for Java, Clojure,Scala
* [JAVA-ML](http://java-ml.sourceforge.net/) - A general ML library with a common interface for all algorithms in Java
* [JSAT](https://code.google.com/p/java-statistical-analysis-tool/) - Numerous Machine Learning algoirhtms for classification, regresion, and clustering.
* [Mahout](https://github.com/apache/mahout) - Distributed machine learning
* [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.
* [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.
* [WalnutiQ](https://github.com/WalnutiQ/WalnutiQ) - object oriented model of the human brain
* [Weka](http://www.cs.waikato.ac.nz/ml/weka/) - Weka is a collection of machine learning algorithms for data mining tasks
#### Speech Recognition
* [CMU Sphinx](http://cmusphinx.sourceforge.net/) - Open Source Toolkit For Speech Recognition purely based on Java speech recognition library.