This course provides an introduction to machine learning and statistical pattern recognition. Topics include: (1) Pattern recognition basics and theory. (2) Supervised learning ideas and methods. (3) Unsupervised learning ideas and some relevant methods. (4) Machine learning workflows and best practices. The course will also cover relevant success stories, and possible applications and case studies in the fields of robotics and smart industrial automation
Ricevimento: All lecture days after class (approx. 20 min). Upon prior agreement, at any other time.
STEFANO ROVETTA (President)