Introduction to Machine Learning and Probabilistic Programming


A high level introduction to machine learning. We work through an example of using linear regression in practice, touching on feature selection, bits of linear algebra, a smidge of optimization, and model evaluation. Uses linear regression to motivate thinking about classification, and gives an advertisement for probabilistic programming.

Cambridge, MA