Using a dataset comprised of songs of two music genres (Hip-Hop and Rock), I trained a classifier to distinguish between the two genres based only on track information derived from Echonest (now part of Spotify). I used pandas and seaborn in Python for subsetting the data, aggregating information, and creating plots when exploring the data for obvious trends or factors..
Next, I used scikit-learn to predict whether I can correctly classify a song's genre based on features such as danceability, energy, acousticness, tempo, etc. I go over implementations of common algorithms such as PCA, logistic regression, decision trees, and so forth.