Great Papers:
http://www.iro.umontreal.ca/~ bengioy/papers/ftml.pdf
http://deeplearning.net/ reading-list/
http://www.iro.umontreal.ca/~
http://deeplearning.net/
Tutorials:
TensorFlow:
https://www.tensorflow.org/
Theano:
http://deeplearning.net/
http://deeplearning.stanford.
Important Names and associated tutorials/talks:
Hinton:
https://www.cs.toronto.edu/~ hinton/nntut.html
LeCun:
http://www.cs.nyu.edu/~yann/ talks/lecun-ranzato-icml2013. pdf
Socher:
http://www.socher.org/index. php/DeepLearningTutorial/ DeepLearningTutorial
https://www.cs.toronto.edu/~
LeCun:
http://www.cs.nyu.edu/~yann/
Socher:
http://www.socher.org/index.
Common Datasets:
IMAGENET - http://www.image-net.org/ challenges/LSVRC/
Courses:
https://www.udacity.com/ course/deep-learning--ud730 - Basic but uses TensorFlow, good to get a basic understanding
https://www.coursera.org/ course/neuralnets - Provides great intuition, a little more challenging
https://cs231n.github.io/ - Great for understanding deep learning for images
https://www.udacity.com/
https://www.coursera.org/
https://cs231n.github.io/ - Great for understanding deep learning for images
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