The document discusses using machine learning techniques to classify music based on audio features extracted from MP3 files. It outlines a multi-step process: 1) Extracting rhythm and timbre features from MP3 files. 2) Storing the features in HBase for distributed processing. 3) Training models on the features using an algorithm like gradient descent. 4) Classifying new music based on the trained models and displaying the results. The goal is to teach machines to classify music by genre based on audio characteristics.