Master (Laurea Magistrale) in: Artificial Intelligence and Robotics
Course begins September, 24 2018,
ends December 22.
Tuesday 15:00 - 18:00 - A17 - SPV
Wedneday 16:00 - 18:00 Axx - SPV
Tools - FTP download
International labs link
This course introduces neural networks which, unlike hard computing, are tolerant of imprecision, uncertainty and partial truth. Topics include: neural networks model, architectures, mathematical property and learning algorithms; optimization algorithms for soft computing methods; application on intelligent data analysis, patterns recognition, multi-sensors data-fusion, blind source separation.
The educational objectives include the acquisition of the following skills: 1) knowledge and understanding of the problems related to the use of NNs; 2) the ability to apply knowledge on NNs in the most common problems described in the course (knowledge and know-how), 3) development of independent judgment regarding the possible optimal solution with NNs of a given problem, 4) the development of communication skills on the topics covered in the course, 5) the ability to autonomous learning on specialized texts.
Final exam modalities
After the study of the course material and a preliminary discussion with the teacher, the examination consists in the discussion of an assigned home work.
The course will be taught in English