Scheda insegnamento

Anno Accademico 2022/2023

Conoscenze e abilità da conseguire

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.


Advanced concepts of Applied Machine Learning. Another more introductory course with basic concepts (Applied Machine Learning - BASIC) is suggested as introduction to this course.

Metodi didattici

Slides and interactive notebooks.

Modalità di verifica e valutazione dell'apprendimento

Written exam and coding project.

Orario di ricevimento

Consulta il sito web di Daniele Bonacorsi