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# Resources for Machine Learning & Deep Learning
#### Examples in this repositoru
## Pratical Examples in this repository
* [Tensorflow examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/TensorFlow): examples in TF.
* [Caffe examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Caffe): examples in Caffe.
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* [ML Notebooks](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Notebooks): jupyter notebooks with ML examples.
* [Numpy examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy): some snippets in Numpy.
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## Learning Resources
### Introductory Courses
### Machine Learning Courses
* [Stanford's Machine Learning Course](http://cs229.stanford.edu/)
* [Google's Developer Machine Learning Course](https://developers.google.com/machine-learning)
* [Stanford's Machine Learning Course](http://cs229.stanford.edu/).
* [Google's Developer Machine Learning Course](https://developers.google.com/machine-learning).
* [Deep Learning Lectures by Lex Fridman](https://www.youtube.com/watch?v=O5xeyoRL95U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf).
### Deep Learning
### Deep Learning Courses
* [Andrew Ng's deeplearning.ai](https://www.deeplearning.ai/deep-learning-specialization/)
* [A Chart of Neural Networks](http://www.asimovinstitute.org/neural-network-zoo/).
* [UCL Course on RL](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html)
* [Stanford's Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu/)
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* [DeepBench](https://github.com/baidu-research/DeepBench).
* [Deep Fake source code](https://github.com/deepfakes/faceswap/).
### Books
* [Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org/).
----
### Tools
#### Deep Learning Tools
* [Tensorflow plaground](http://playground.tensorflow.org).
* [Google's Tensorflow courses](https://www.tensorflow.org/).
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## Articles
* [MIT Deep Learning Basics](https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0).
## Lectures