Self-directed exploration of classical machine learning algorithms for HMC's CS189 Programming Practicum elective. Particular focus was given to regression algorithms, as I was working with continuous variables.
Project goal: understand how classical machine learning algorithms work, and apply them to predict air pollution levels on the ground, based on weather data and satellite observations of pollutants. Dataset from Zindi.
Future areas of exploration: algorithms that can operate on time series data to take advantage of time and location features (rather than treating data as independent entries in a table).