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# Resources for Machine Learning # Resources for Machine Learning
## Tools ## In this Repositoryy
* [Tensorflow](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/TensorFlow). * [Tensorflow](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/TensorFlow): examples in TF.
* [Caffe](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Caffe). * [Caffe](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Caffe): examples in Caffe.
* [Talks](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Talks). * [DeepArt](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy): deep learning generated art.
* [Notebooks](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Notebooks). * [ML Notebooks](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Notebooks): jupyter notebooks with ML examples.
* [Docker images](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Docker_Images). * [Numpy examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy): some snippetes in Numpy.
* [Numpy](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy).
----
## Learning ## Learning
### Courses ### Introductory Courses
* [Stanford's Machine Learning Course](http://cs229.stanford.edu/) * [Stanford's Machine Learning Course](http://cs229.stanford.edu/)
* [Google's Developer Machine Learning Course](https://developers.google.com/machine-learning) * [Google's Developer Machine Learning Course](https://developers.google.com/machine-learning)
## Deep Learning ### Deep Learning
* [A Chart of Neural Networks](http://www.asimovinstitute.org/neural-network-zoo/). * [A Chart of Neural Networks](http://www.asimovinstitute.org/neural-network-zoo/).