CS501r, Fall 2017 - Deep Learning: Theory and Practice

Here is the course description.

Remember, this is a great tutorial on python / numpy!

Some instructions for getting Tensorflow to run on the CS open labs

All of the slides are posted on Dropbox here

A quick intro to deep learning on the supercomputer

A quick intro to deep learning on google cloud

A nice tutorial on setting up wsl for machine learning


Labs

General notes on ipython and seaborn

Lab 1 - Anaconda and playground screenshot

Lab 2 - Perceptron

Lab 3 - Gradient descent

Lab 4 - Get to know tensorflow

Lab 5 - Your first Tensorflow image classifier

Lab 6 - Cancer detector

Lab 7 - Generative adversarial networks

Lab 8 - RNNs, LSTMs, GRUs

Lab 9 - Siamese networks

Lab 10 - Inceptionism / deep art

Lab 11 - Neural machine translation

Final project

Old labs that we probably won't use

Lab 6 - Feature zoo 1

Lab 5b - Convolutional Tensorflow image classifier and Tensorboard