Difference between revisions of "Machine Learning"
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- [https://www.coursetalk.com/providers/coursera/courses/neural-networks-for-machine-learning Intro vid for course] | - [https://www.coursetalk.com/providers/coursera/courses/neural-networks-for-machine-learning Intro vid for course] | ||
- [http://www.cs.toronto.edu/~hinton/ Hinton's homepage] | - [http://www.cs.toronto.edu/~hinton/ Hinton's homepage] | ||
| + | - [https://www.norsys.com/tutorials/netica/secA/tut_A1.htm Bayesian Nets Tutorial] -- helpful for later parts of Hinton | ||
[https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu Deep learning at Oxford 2015 (Nando de Freitas)] | [https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu Deep learning at Oxford 2015 (Nando de Freitas)] | ||
Revision as of 14:41, 21 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)
