Helpful_Links.txt

Video explaining basics of neural network and backpropogation:
https://www.youtube.com/watch?v=WZDMNM36PsM

Introduction to neural networks:
http://neuralnetworksanddeeplearning.com/chap1.html

Great explanation of backpropogation:
http://neuralnetworksanddeeplearning.com/chap2.html

Improving neural networks:
http://neuralnetworksanddeeplearning.com/chap3.html

Hyper-parameter selection:
https://arxiv.org/abs/1206.5533

Deep neural networks (in particular convolutional image-detection):
http://neuralnetworksanddeeplearning.com/chap6.html

Great explanation of RNNs, including visualization:
https://deeplearning4j.org/lstm.html#recurrent

TensorFlow programmer's guide:
https://www.tensorflow.org/programmers_guide/

Recurrent Neural Networks:
http://colah.github.io/posts/2015-08-Understanding-LSTMs/

Effectiveness of RNNs: (incredible)
http://karpathy.github.io/2015/05/21/rnn-effectiveness/

Description of Preconditioners:
http://www.mathcs.emory.edu/~benzi/Web_papers/survey.pdf

Preconditioned Conjugate Gradient in MATLAB:
https://www.mathworks.com/help/matlab/ref/pcg.html