Introduction to Machine Learning

This course teaches the fundamentals of algorithms, principles, and the application of machine-learning from the perspective of prediction and modeling. It covers the formulating learning problems as well as notions that deal with representations, over-fitting, and generalization. These concepts are applied in the areas of reinforcement and supervised learning, and are applied to pictures and temporal sequences.