Practical Machine Learning - Deep Learning

Lecturer: Jian Li

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Oct 7 Basics - Logistic regression, SVM, Gradient Descent, Stochastic GD, Neural Networks, Back Propagation, Training Tricks slides
Oct 21 CNN, PCA, Several CNN architectures, Visualize CNN (deconv net), Deep Dream, Neural Art slides
Oct 28 RNN, Bidirectional RNN, Grad vanishing & Explosion, LSTM, Image Captioning slides
Nov 3 Autoencoder, Attention (spatial transformer), Multi-modal learning, Neural Turing Machine, Memory Networks, Generative Adversarial Net slides

Links:

CS224d: Deep Learning for Natural Language Processing

http://cs224d.stanford.edu/reports_2016.html

CS231n: Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/project.html

Nando de Freitas¡¯s class at Oxford 

https://www.cs.ox.ac.uk/people/nando.defreitas/machinelearning/

Jeff Hinton's Deep Learning Course

Deepmind

https://deepmind.com/research/publications/

Deep Learning Book (Ian Goodfellow and Yoshua Bengio and Aaron Courville)

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