Neural Networks
From Robin
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==Presentations== | ==Presentations== | ||
| - | * [https://docs.google.com/presentation/d/e/2PACX-1vTpAadWGnccwlDdXOdNpPSwagLWFakcXQwd0XlVfOuZvTDNVSFJNTISLTz8CFBmip7a0_fUcihUV29J/pub] | + | * [https://docs.google.com/presentation/d/e/2PACX-1vTpAadWGnccwlDdXOdNpPSwagLWFakcXQwd0XlVfOuZvTDNVSFJNTISLTz8CFBmip7a0_fUcihUV29J/pub Slides: RNNs, LSTMs, and MDNs (Charles Martin, 6/11/2017] |
==Resources== | ==Resources== | ||
Revision as of 14:54, 6 November 2017
Here we will gather useful information and resources for learning about and using neural networks. Feel free to add information here!
Contents |
Presentations
Resources
Software
- Tensorflow - numerical computation software, great for defining ANNs.
Books
- Deep Learning (Ian Goodfellow, Yoshua Bengio and Aaron Courville): https://github.com/HFTrader/DeepLearningBook
- Hands-On Machine Learning with Scikit-Learn and TensorFlow
- http://statweb.stanford.edu/~tibs/ElemStatLearn/printings/ESLII_print10.pdf
