Notes from David Ben Shimol's talk at CODE on "Machine Learning: a shallow intro to deep learning" March 22, 2016.
- Tutorials: http://Deeplearning.net
- Hardware guide: http://timdettmers.com/2015/03/09/deep-learning-hardware-guide
- Hinton @ Coursera: http://coursera.org/course/neuralnets
- LeCun @ NYU: http://cilvr.cs.nyu.edu/doku.php?id=courses:deeplearning2014:start
- Socher @ Stanford (NLP): http://cs224d.stanford.edu
- Nando de Freitas @ Oxford: https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu
- Nvidia: http://developer.nvidia.com/deep-learning-courses
- TensorFlow @Udacity: https://www.udacity.com/course/deep-learning--ud730
- Google+ community: http://plus.google.com/communities/112866381580457264725
- http://github.com/ChristosChristofidis/awesome-deep-learning
- Vision: http://jiwonkim.org/awesome-deep-vision
- RNN: http://jiwonkim.org/awesome-rnn
- Bengio’s et al., http://goodfeli.github.io/dlbook.
- Jeff Hawkins: On Intelligence
In addition, if anyone wants to experiment on a GPU, get more details or bounce of some ideas I’m available at dbenshimol@mba2016.hbs.edu.