Machine Learning: an overview

The course "Machine Learning: an overview" offered by Politecnico di Milano, delivers a comprehensive introduction to the core methods in the field of machine learning. Students will gain a broad understanding of the various problems that can be addressed through machine learning techniques and the algorithms that underpin them.

Throughout the course, participants will delve into the taxonomy of machine learning problems, distinguishing between supervised and unsupervised learning, and exploring the limitations of these techniques. Real-world examples and case studies will be used to illustrate the practical application of these concepts, providing valuable insights into when and how to employ different approaches.

Key topics covered include:

• Classification of machine learning problems
• Utility of dimensionality reduction techniques
• Formulation of sequential decision-making problems
• Optimization of policies in reinforcement learning

By the end of the course, participants will be equipped with the knowledge and skills to classify machine learning problems, understand the limitations of supervised learning, and utilize techniques such as dimensionality reduction and reinforcement learning in practical scenarios.