AIMS AND CONTENT

LEARNING OUTCOMES

Learning how to use advanced machine learning algorithms, including learning data representation (dictionaries and metric), deep learning, and learning in dynamic environment (online, active and reinforcement learning), by grasping the underlying computational and modeling issues.

PREREQUISITES

The material covered in the Machine learning Course.

TEACHING METHODS

Classes and practical labs. 

SYLLABUS/CONTENT

The course covers a range of diverse topics including  learning data representation (dictionaries and metric), deep learning, and learning in dynamic environment (online, active and reinforcement learning).

RECOMMENDED READING/BIBLIOGRAPHY

Distributed in class. 

TEACHERS AND EXAM BOARD

Exam Board

LORENZO ROSASCO (President)

ANNALISA BARLA (President Substitute)

NICOLETTA NOCETI (President Substitute)

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

Exam schedule