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61 lines
2.2 KiB
Markdown
61 lines
2.2 KiB
Markdown
# Resources for Machine Learning & Deep Learning
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## Pratical Examples in this repository
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* [Tensorflow examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/TensorFlow): examples in TF.
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* [Caffe examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Caffe): examples in Caffe.
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* [DeepArt examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy): deep learning generated art.
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* [ML Notebooks](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Notebooks): jupyter notebooks with ML examples.
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* [Numpy examples](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Numpy): some snippets in Numpy.
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---------
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## Learning Resources
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### Machine Learning Courses
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* [Stanford's Machine Learning Course](http://cs229.stanford.edu/).
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* [Google's Developer Machine Learning Course](https://developers.google.com/machine-learning).
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* [Deep Learning Lectures by Lex Fridman](https://www.youtube.com/watch?v=O5xeyoRL95U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf).
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### Deep Learning Courses
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* [Andrew Ng's deeplearning.ai](https://www.deeplearning.ai/deep-learning-specialization/)
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* [A Chart of Neural Networks](http://www.asimovinstitute.org/neural-network-zoo/).
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* [UCL Course on RL](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html)
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* [Stanford's Convolutional Neural Networks for Visual Recognition](http://cs231n.stanford.edu/)
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* [The 9 CNN Papers You Need To Know About](https://adeshpande3.github.io/adeshpande3.github.io/The-9-Deep-Learning-Papers-You-Need-To-Know-About.html).
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* [NVIDIA Deep Learning Course](https://www.youtube.com/playlist?list=PL5B692fm6--tI-ijknnVZWbXU2H4JpSYe)
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* [DeepBench](https://github.com/baidu-research/DeepBench).
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* [Deep Fake source code](https://github.com/deepfakes/faceswap/).
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### Books
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* [Deep Learning by Ian Goodfellow and Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org/).
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----
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### Tools
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#### Deep Learning Tools
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* [Tensorflow plaground](http://playground.tensorflow.org).
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* [Google's Tensorflow courses](https://www.tensorflow.org/).
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----
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## Articles
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* [MIT Deep Learning Basics](https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0).
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## Lectures
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