dl_workshop

Deep Learning Training

Suggested Reads:

• Efficient Backprop: http://yann.lecun.com/exdb/publis/pdf/lecun-98b.pdf
• Practical Recommendations for Deep Architectures: https://arxiv.org/pdf/1206.5533v2.pdf
• Word Vectors(Mukul's Medium Post): https://medium.com/@mukulmalik/word2vec-part-1-fe2ec6514d70

Links to Slides:

• NLP Basics: https://docs.google.com/presentation/d/1Yi-ColCsDTPVnCmAPq7Ia-z2A4oF1VQKPtFRojnBqnY/edit?usp=sharing
• Intro to Neural Networks: https://docs.google.com/presentation/d/1tj4ROGdDDv9j5V372AIXYrAKk6Sx8bZyFBtEgez--fw/edit?usp=sharing

Reads for future sessions:

• Understanding LSTM Networks: http://colah.github.io/posts/2015-08-Understanding-LSTMs/

• RNN Tutorial(Denny Britz): http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/

• Understanding CNNs for NLP: http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/

• The unreasonable effectiveness of RNNs: http://karpathy.github.io/2015/05/21/rnn-effectiveness/