Difference between revisions of "Machine Learning"
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+ | http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ <-- Great article! |
Revision as of 23:45, 22 August 2016
Tuts
UFLDL Stanford (Deep Learning) Tutorial
Principles of training multi-layer neural network using backpropagation <-- Great visual guide!
Courses
Neural Networks for Machine Learning — Geoffrey Hinton, UToronto
- Coursera course - Vids (on YouTube - Intro vid for course - Hinton's homepage - Bayesian Nets Tutorial -- helpful for later parts of Hinton
Deep learning at Oxford 2015 (Nando de Freitas)
Notes for Andrew Ng's Coursera course.
Papers
Applying Deep Learning To Enhance Momentum Trading Strategies In Stocks
- Hinton (2010) -- A Practical Guide to Training Restricted Boltzmann Machines - Hinton, Salakhutdinov (2006) -- Reducing the Dimensionality of Data with Neural Networks
Books
Nielsen -- Neural Networks and Deep Learning <-- online book
http://www.deeplearningbook.org/
S/W
http://playground.tensorflow.org
SwiftNet <-- My own back propagating NN (in Swift)
Misc
Links: https://github.com/memo/ai-resources
http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/ <-- Great article!