During my Ph.D., I utilized a U-Net to attempt to learn the final distribution of dark matter in a computer simulation from its initial conditions. Being in an Astrophysics Ph.D. program, and the year being 2020, model architectures like the U-Net weren’t well known by people in my field, including my Ph.D. advisor. He tasked me: teach him what it was, down to the details, so that he could understand the concepts at a deep enough level himself to help properly guide me on the project.
And thus, my first Jupyter notebook tutorial was born. In the process of writing code cells, making graphics in powerpoint, and scouring through documentation, I found an even deeper understanding of the concepts I was describing. As they say, the best way to prove you really know something is to teach it. Since then, every time I really want to understand something, I make a Jupyter notebook tutorial about it.
It occured to me (5 years later), that maybe someone else would care to read these. So here, you’ll find a collection of the notebooks that I’ve put together. Mainly to teach myself, but hopefully, to teach you too!