pytorch variational autoencoder documentation example
Refactoring the PyTorch Variational Autoencoder Documentation Example
There's no universally best way to learn about machine learning. But one of my most common techniques is to find a code example of whatever new topic I'm interested in, get the example to run, then refactor the working example to a simpler form. Refactoring code forces me to examine every line of code and make sure I understand it (well, for the most part anyway). I applied this learning strategy to variational autoencoders using the PyTorch neural library. The documentation demo creates a variational autoencoder that generates synthetic MNIST digits from '0' to '9'.