Deep Learning with Applications

A.Y. 2021/2022
6
Max ECTS
42
Overall hours
SSD
FIS/02
Language
Italian
Learning objectives
The course presents Deep Learning from a theoretical and practical point of view, introduces the basic elements of learning (non-linear models, minimization techniques, cross-validation and hyper-parameter tuning) and focuses on supervised, unsupervised and reinforcement learning models
Expected learning outcomes
At the end of the course the student will be able to:

- illustrate deep learning models in the learning context
supervised, unsupervised and for reinforcement.

- identify deep learning models suitable for the resolution of
problems in physics and beyond.

- use software and libraries for the development of deep learning models.
Single course

This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.

Course syllabus and organization
Professor(s)
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