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