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ML, neural networks, and deep learning python libraries
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specializations.md

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@@ -7,6 +7,18 @@ _[Note: I'm adding this section due to the overwhelming amount of input from new
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* Neural Networks for Machine Learning [U Toronto / Coursera](https://www.coursera.org/course/neuralnets)
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* [Building Machine Learning Systems with Python](http://www.packtpub.com/building-machine-learning-systems-with-python/book) [source code](https://github.com/luispedro/BuildingMachineLearningSystemsWithPython)
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Packages
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* [mlpy](http://mlpy.sourceforge.net) Machine Learning Python
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* Machine Learning Toolkit [MILK](http://packages.python.org/milk/)
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* [MDP](https://pypi.python.org/pypi/MDP) a collection of supervised and unsupervised learning algorithms
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* [pyBrain](http://pybrain.org/) modular Machine Learning Library for Python
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* [Caffe](http://caffe.berkeleyvision.org/) framework for convolutional neural network algorithms
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* [Nolearn](https://pypi.python.org/pypi/nolearn) framework wrapping scikit neural networks
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* [OverFeat](http://cilvr.nyu.edu/doku.php?id=software:overfeat:start) Convolutional Network-based image features extractor and classifier
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* [Hebel](https://github.com/hannes-brt/hebel) GPU-Accelerated Deep Learning Library in Python
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* [neurolab](https://code.google.com/p/neurolab/) simple and powerful Neural Network Library for Python. Contains based neural networks, train algorithms and flexible framework to create and explore other networks
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* [Pylearn2](http://deeplearning.net/software/pylearn2/) and [Theano](http://deeplearning.net/software/theano/) deep learning libraries
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#### Deep Learning
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[Wikipedia Definition](http://en.wikipedia.org/wiki/Deep_learning)

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