Intro to Deep Learning from the Foundations, in Elixir

Developing a set of notebooks to follow the Deep Learning from the Foundations to Stable Diffusion Course

I’ve started a project on GitHub, dl_foundations_in_elixir. In this project, I collect the Elixir Livebook notebooks that I will create while taking the From Deep Learning Foundations to Stable Diffusion, Practical Deep Learning for Coders part 2, 2022. The course is happening live for the past three weeks, so far.

The content of the course is in two parts. We are exploring Stable Diffusion as it exists today and we are exploring the latest papers that improve or explore Stable Diffusion related concepts. We are learning the skills to read the math in the papers, what parts of a paper are most useful to explore in depth and gaining confidence in reading papers. So far, 4 hours of the main lesson by Jeremy have been focused here. There are additional videos by community members that expand upon the main lessons.

For each of the past two weeks, Jeremy has been exploring the 01_matmul Python/Jupyter notebook. We aren’t quite done with the notebook just yet. We are just about to transition from CPU focused cells to running a matrix multiplication on the GPU. I’ve released an Elixir/Livebook version of the notebook called, 01a_matmul_using_CPU.livemd. I’m focused on the CPU portions of the notebook. Where there is a direct mapping from the Python cell to my Elixir cell, I provide the Python and the Elixir in one cell. Elixir developers can see how Python machine learning methods get translated into Elixir modules. Please checkout our progress so far. We are open to pull requests and the discussion capabilities of Github are available.

Run in Livebook

Next, I’ve created a Livebook notebook where I try to help PyTorch/Jupyter developers that are exploring Elixir/Livebook with key aspects of Livebook, . In a short notebook, I explain some of the key differences with Elixir and Livebook. Again, we are open to pull requests and discussion.

Run in Livebook

fastai, axon, foundations, deep_learning