Links

RESOURCES & LINKS

The following list contains several links of interest:

---------------------------------------------------------------------------------------------------------------------------------

Deep Learning Resources
- Deep Learning Review at Nature
- The Deep Learning online textbook by I. Goodfellow, Y. Bengio and A. Courville (MIT Press)
- Dive into Deep Learning : Interactive deep learning book with code, math, and discussions
- Neural Networks for Machine Learning course by G. Hinton on Coursera or YouTube
- Machine Learning course by A. Ng on YouTube or Coursera
- DeepLearning Tutorial @ UFLDL : Regression, MLP, Supervised-CNN, Unsupervised-AE
- Tutorial @ deeplearning.net : MLP, CNN, AE, RBM, DBN, RNN
- Understanding LSTMs: An Insight
- Alex Graves's homepage : Recurrent Networks (LSTM)
- KNet on Julia @ GitHub (D. Yuret)
- ConvNetJS: Online Java Script Library for Convolutional Nets
- CS231n: Convolutional Networks for Visual Recognition (Stanford)
- Awesome Deep Learning at GitHub
- Awesome RNNs @ GitHub
Awesome Machine Learning @ GitHub
Awesome Information Retrieval @ GitHub
Awesome Computer Vision @ GitHub
Awesome Deep Vision @ Github
Computer Vision Compendium online
IEEE SP Machine Learning for Signal Processing Committee
Probabilistic Graphical Models course on YouTube or Coursera
Matlab webinar on Signal Processing and Machine Learning Techniques for Sensor Data Analytics