Basics of getting setup w/ tensorflow and graph computation.
Performing regression with a single factor and bias.
Performing regression using polynomial factors.
Performing logistic regression using a single layer neural network.
Building a deep convolutional neural network.
Building a deep convolutional neural network w/ batch normalization and leaky rectifiers.
Building a deep autoencoder w/ tied weights.
Building a deep denoising autoencoder which corrupts the input.