Optimization

This tutorial provides a step-by-step guide to implementing Bayesian optimization from scratch. The Overall story is that we want to find the global minimum/maximum of an unknown function. The procedure consists of first fitting a Gaussian process to the existing samples from the objective function and through that fitted model, finding the most suitable next point to be sampled. Source Github Repo introduction This tutorial assumes that you are already familiar with the following concepts:...