====CS501r, Fall 2016 - Deep Learning: Theory and Practice====

[[cs501r_f2016:desc|Here is the course description.]]

[[http://cs231n.github.io/python-numpy-tutorial/|Remember, this is a great tutorial on python / numpy!]]

[[cs501r_f2016:openlabtf|Some instructions for getting Tensorflow to run on the CS open labs]]

[[https://www.dropbox.com/sh/aox63ppfd14hf7b/AABGgv56Q98ikk5I8I4bNbO3a?dl=0|All of the slides are posted on Dropbox here]]

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=== Labs ===

[[cs501r_f2016:lab_notes|General notes on ipython and seaborn]]

[[cs501r_f2016:lab1|Lab 1 - Anaconda and playground screenshot]]

[[cs501r_f2016:lab2|Lab 2 - Perceptron]]

[[cs501r_f2016:lab3|Lab 3 - Basic gradient descent]]

[[cs501r_f2016:lab4|Lab 4 - Automatic differentiation]]

[[cs501r_f2016:lab5|Lab 5 - Tensorflow image classifier]]

[[cs501r_f2016:lab5b|Lab 5b - Convolutional Tensorflow image classifier and Tensorboard]]

[[cs501r_f2016:lab6|Lab 6 - Feature zoo 1]]

[[cs501r_f2016:lab7|Lab 7 - Generative adversarial networks]]

[[cs501r_f2016:lab10|Lab 8 - RNNs, LSTMs, GRUs]]

[[cs501r_f2016:lab9|Lab 9 - Siamese networks]]

[[cs501r_f2016:lab13|Lab 10 - Inceptionism / deep art]]


[[cs501r_f2016:fp|Final project]]