Course Highlights

• Machine Learning is the study of how to build computer systems that learn from experience. It is a subfield of Artificial Intelligence and intersects with cognitive science, information theory, and probability theory, among others. The course will explain how to build systems that learn and adapt using real-world applications from industry and science (e.g., learning to classify astronomical objects, to predict medical diagnoses, to play chess).

Topics

• Concept learning

• Hypothesis spaces

• Decision trees

• Neural networks

• Bayesian learning

• Computational learning theory

• Instance-based learning

• Genetic algorithms

• Rule-based learning

• Analytical learning

• Reinforcement learning

Labwork

• two midterm exams,

• a final exam,

• homework assignments

• A final project that involves some amount of programming