This is a project to see if anything can be learnt by drawing parallels between human color perception and neural networks trained for vision tasks.
The evidence lower bound expression appears naturally when you try to sample the posterior distribution with an approximate distribution. I think this way of arriving at the evidence lower bound is more intuitive and reveals more about why concessions are being made.
Some videos showing how weights, activations and gradients change at every step as a network is trained.
I've exported some of my Anki decks. Most of the content is on the answer side of each card. If you aren't using Anki, I invite you to read Michael Nielsen's argument for it.
2021's Summer of Math Exposition
The following are some posts made for 3Blue1Brown's Summer of Math Exposition. They are attempts to make clear and memorable math explainers for a wide audience.