For May, I set out to do a machine learning course in R, and I identified a DataCamp course to take.

Originally, I set out to complete one module per week. However, in the end, I completed one module total – one chapter per week. Each chapter of the module is a different supervised machine learning algorithm, and this made it easy to digest.

There were three weeks left in the month after I identified the module, and thus I learned three algorithms.

Week 1: K-Nearest Neighbors

Week 2: Bayesian Methods

Week 3: Decision Trees and Random Forest

Onward to June.