Course Unit Page

Academic Year 2020/2021

Learning outcomes

At the end of the course the student is able to handle different Machine Learning and Deep Learning models, to tune them to specific applications, and to design approaches that may scale with large amount of data. Moreover, the student has competences on how to exploit different hardware architectures for Machine Learning and Deep Learning solutions, both on-premise and via cloud. The student will be also introduced to most recent approaches and active areas of work in the Artificial Intelligence community worldwide.

Course contents

Advanced concepts of Applied Machine Learning.

Office hours

See the website of Daniele Bonacorsi