Autoencoders

In this lesson we're covering autoencoders. These models are used to compress data, as well as image denoising, which you'll be implementing in this lesson. The idea here is we'll build a network that tries to generate it's input data, but with a narrow hidden layer that serves as a compressed representation of the input data.

As a heads up, the lesson structure will be a bit different than you've seen before. Here I'll be walking you through implementing autoencoders in a Jupyter Notebook. You can find the notebooks for this lesson in our public GitHub repo, in the autoencoder directory. Do a git pull to get the most recent files!

Or, clone the repo with

git clone https://github.com/udacity/deep-learning.git

You can get the files directly here.