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README.md

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@@ -744,11 +744,11 @@ Inspired by [awesome-php](https://github.com/ziadoz/awesome-php).
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*Libraries for Machine Learning. See: [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning#python).*
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* [gensim](https://github.com/piskvorky/gensim) - Topic Modelling for Humans.
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* [gensim](https://github.com/RaRe-Technologies/gensim) - Topic Modelling for Humans.
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* [LightFM](https://github.com/lyst/lightfm) - A Python implementation of a number of popular recommendation algorithms.
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* [MLlib](http://spark.apache.org/mllib/) - [Apache Spark](http://spark.apache.org/)'s scalable Machine Learning library.
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* [NuPIC](https://github.com/numenta/nupic) - Numenta Platform for Intelligent Computing.
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* [scikit-learn](http://scikit-learn.org/) - The most popular Python library for Machine Learning.
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* [Spark ML](http://spark.apache.org/docs/latest/ml-guide.html) - [Apache Spark](http://spark.apache.org/)'s scalable Machine Learning library.
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* [surprise](http://surpriselib.com) - A scikit for building and analyzing recommender systems.
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* [vowpal_porpoise](https://github.com/josephreisinger/vowpal_porpoise) - A lightweight Python wrapper for [Vowpal Wabbit](https://github.com/JohnLangford/vowpal_wabbit/).
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* [xgboost](https://github.com/dmlc/xgboost) - A scalable, portable, and distributed gradient boosting library.

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