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新增 Pytorch,Theano,Mxnet 三个深度学习库
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README.md

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* gensim:人性化的话题建模库。[官网](https://github.com/piskvorky/gensim)
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* hebel:GPU 加速的深度学习库。[官网](https://github.com/hannes-brt/hebel)
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* [keras](https://github.com/keras-team/keras): 以 tensorflow/theano/CNTK 为后端的深度学习封装库,快速上手神经网络。[官网](https://keras.io/)
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* [MXNet](https://github.com/apache/incubator-mxnet):一个高效和灵活的深度学习框架。[官网](http://mxnet.incubator.apache.org/)
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* NuPIC:智能计算 Numenta 平台。[官网](https://github.com/numenta/nupic)
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* pattern:Python 网络挖掘模块。[官网](https://github.com/clips/pattern)
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* [PyBrain](http://hao.jobbole.com/pybrain/):另一个 Python 机器学习库。[官网](https://github.com/pybrain/pybrain)
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* pydeep:Python 深度学习库。[官网](https://github.com/andersbll/deeppy)
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* [Pylearn2](http://hao.jobbole.com/pylearn2/):一个基于 [Theano](https://github.com/Theano/Theano) 的机器学习库。[官网](https://github.com/lisa-lab/pylearn2)
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* [python-recsys](http://hao.jobbole.com/python-recsys/):一个用来实现推荐系统的 Python 库。[官网](https://github.com/ocelma/python-recsys)
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* pydeep:Python 深度学习库。[官网](https://github.com/andersbll/deeppy)
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* [Pytorch](https://github.com/pytorch/pytorch):一个具有张量和动态神经网络,并有强大 GPU 加速能力的深度学习框架。[官网](http://pytorch.org/)
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* scikit-learn:基于 SciPy 构建的机器学习 Python 模块。[官网](http://scikit-learn.org/)
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* skflow:一个 [TensorFlow](https://github.com/tensorflow/tensorflow) 的简化接口(模仿 scikit-learn)。[官网](https://github.com/tensorflow/skflow)
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* [TensorFlow](https://github.com/tensorflow/tensorflow):谷歌开源的最受欢迎的深度学习框架。[官网](http://tensorflow.org/)
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* Theano:一个快速数值计算库。[官网](https://github.com/Theano/Theano)
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* vowpalporpoise:轻量级 [Vowpal Wabbit](https://github.com/JohnLangford/vowpalwabbit/) 的 Python 封装。[官网](https://github.com/josephreisinger/vowpalporpoise)
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### MapReduce

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