A explanation of Gaussian processes and Gaussian process regression, starting with simple intuition and building up to inference. I sample from a GP in native Python and test GPyTorch on a simple simulated example.

I trained a classifier on images of animals and gave it an image of myself, it's 98% confident I'm a dog. This is an exploration of a possible Bayesian fix. Code available too

The Beta and Dirichlet distributions are related to each other in a similar way to the Binomial and Multinomial distributions. This post explains the relationship between these 4 distributions using a simple example and some code.