Tools and applications of machine learning

Alessandro Sperduti
Dipartimento di Informatica

The aim of the course is to introduce, from a practical point of view, the student to basic machine learning tools and their use. Specifically, the student will learn when it is reasonable to use machine learning tools, what are the basic constituents of a machine learning tool, which type of tasks can they achieve, how to evaluate their performance. Both supervised and unsupervised tools will be introduced. Examples of applications of the tools will be given. Finally, cognitive services based on machine learning tools will be presented and their application demonstrated.

- Introduction to machine learning tools and their correct use.
- What can machine learning tools achieve: supervised vs unsupervised techniques.
- Examples of application and how to assess performances.
- Introduction to cognitive services.

Course requirements
The student is expected to have basic knowledge of probability and programming.

Examination modality
The students will be evaluated on practical projects.

11 June, 10:00-12:00
12 June, 10:00-12:00
14 June, 10:00-13:00
15 June, 10:00-13:00
20 July,  9:00-13:00 (exam)

Meeting room of HIT centre, via Luzzatti 4

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