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32 lines
1.4 KiB
Markdown
32 lines
1.4 KiB
Markdown
# Resources for Machine Learning
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## In this Repositoryy
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* [Tensorflow](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/TensorFlow): examples in TF.
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* [Caffe](https://github.com/bt3gl/Resources-Machine_Learning/tree/master/Caffe): examples in Caffe.
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* [DeepArt](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 snippetes in Numpy.
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## Learning
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### Introductory 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
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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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