Difference between revisions of "Machine Learning"
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[https://www.youtube.com/channel/UCPk8m_r6fkUSYmvgCBwq-sw/playlists Karpathy -- CS231n] | [https://www.youtube.com/channel/UCPk8m_r6fkUSYmvgCBwq-sw/playlists Karpathy -- CS231n] | ||
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| + | === Boltzmann Machines === | ||
| + | Hopfield to Boltzmann http://haohanw.blogspot.co.uk/2015/01/boltzmann-machine.html | ||
| + | Hinton's Lecture, then: | ||
| + | https://en.wikipedia.org/wiki/Boltzmann_machine | ||
| + | http://www.scholarpedia.org/article/Boltzmann_machine | ||
| + | [http://www.cs.toronto.edu/~hinton/absps/guideTR.pdf Hinton (2010) -- A Practical Guide to Training Restricted Boltzmann Machines] | ||
== Papers == | == Papers == | ||
[http://cs229.stanford.edu/proj2013/TakeuchiLee-ApplyingDeepLearningToEnhanceMomentumTradingStrategiesInStocks.pdf Applying Deep Learning To Enhance Momentum Trading Strategies In Stocks] | [http://cs229.stanford.edu/proj2013/TakeuchiLee-ApplyingDeepLearningToEnhanceMomentumTradingStrategiesInStocks.pdf Applying Deep Learning To Enhance Momentum Trading Strategies In Stocks] | ||
| − | + | ||
- [https://www.cs.toronto.edu/~hinton/science.pdf Hinton, Salakhutdinov (2006) -- Reducing the Dimensionality of Data with Neural Networks] | - [https://www.cs.toronto.edu/~hinton/science.pdf Hinton, Salakhutdinov (2006) -- Reducing the Dimensionality of Data with Neural Networks] | ||
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http://karpathy.github.io/2015/05/21/rnn-effectiveness/ | http://karpathy.github.io/2015/05/21/rnn-effectiveness/ | ||
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https://www.youtube.com/watch?v=gfPUWwBkXZY <-- Hopfield vid | https://www.youtube.com/watch?v=gfPUWwBkXZY <-- Hopfield vid | ||
http://www.gitxiv.com/ <-- Amazing projects here! | http://www.gitxiv.com/ <-- Amazing projects here! | ||
Revision as of 09:58, 25 August 2016
Getting Started
DeepLearning.TV YouTube playlist -- good starter!
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) - same, better organized - 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.
Hugo Larochelle: Neural networks class - Université de Sherbrooke
Boltzmann Machines
Hopfield to Boltzmann http://haohanw.blogspot.co.uk/2015/01/boltzmann-machine.html Hinton's Lecture, then: https://en.wikipedia.org/wiki/Boltzmann_machine http://www.scholarpedia.org/article/Boltzmann_machine Hinton (2010) -- A Practical Guide to Training Restricted Boltzmann Machines
Papers
Applying Deep Learning To Enhance Momentum Trading Strategies In Stocks
- Hinton, Salakhutdinov (2006) -- Reducing the Dimensionality of Data with Neural Networks
Books
Nielsen -- Neural Networks and Deep Learning <-- online book
http://www.deeplearningbook.org/
https://page.mi.fu-berlin.de/rojas/neural/ <-- Online book
S/W
http://playground.tensorflow.org
TensorFlow in IPython YouTube (5 vids)
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!
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
https://www.youtube.com/watch?v=gfPUWwBkXZY <-- Hopfield vid
http://www.gitxiv.com/ <-- Amazing projects here!
