Machine Learning for Safety Systems

Course Description and Motivation

The course objective is to provide a general overview of the modern techniques of Machine Learning and their applicability to safety systems. In addition to the description of the foundations of Machine Learning, the course provides the necessary background in order to understand and apply Machine Learning approaches to classification, regression and clustering techniques to solve practical problems in different applicative scenarios by mean of neural networks and other learning techniques. During the course, it will also describe the use of specific software packages, such as WEKA, for the implementation, use and validation of the modern Machine Learning techniques. At the end of the course students will be able to handle different Machine Learning models, to tune them to specific applications, and to design approaches that may scale with large amount of data.


Scientific Sector (SSD)

ING-IND/31 (Electrical Engineering)


Overview and Credits

MSZR; First year; Second semester. 6 CFUs.


Prerequisites

Students are expected to have the following background:


Grading

Project.


Syllabus

Detailed contents.


Suggested Books

Further reading


Time and Location

The course will start on February 28 2023, with the following schedule:


Office Hours

Every day by appointment.


Classroom

News, updates, and communications about the course will be available on Google Classroom, with the code: aqc545a.


Course Materials

Lecture Slides:


Python Source Codes:


Lecture Notes:


Exams Session

The verbalization takes place on the dates indicated below, at the instructor's office:

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 Please, note that the exam is reserved electronically via the INFOSTUD system.