PhD-Summer Course- Jun 5-9 2017 Genoa, Italy



Machine Learning: A Computational Intelligence Approach

MLCI 2017 (5th  edition)


The participation is free, but registration is required:  register HERE  by May 29th, 2017


genoa

Instructors:
Francesco Masulli DIBRIS - UniGe (email: francesco.masulli@unige.it)
Stefano Rovetta
DIBRIS - UniGe (email: stefano.rovetta@unige.it)


Period: Jun 5-9, 2017    (Mon-Thu 11:00 am - 1:00 pm and 2:00 pm - 4:00 pm; Fri 11:00 am - 1:00 pm  only)        `

Number of hours: 18 

Summary: The Computational Intelligence is a set of methodologies for information processing inspired by natural systems that in recent decades have been successfully applied to the solution of complex problems. Among them, one can mention the Neural Networks, the Evolutionary Algorithms, the Swarm Intelligence models, the Simulated Annealing, and the Fuzzy sets and Systems. In this course we present some applications of Computational Intelligence methods to supervised and unsupervised problems of Machine Learning.

Syllabus: Supervised Classification, Neural Networks, Evaluation of Classifiers, Introduction to Clustering, Statistical Clustering, Fuzzy Sets, Fuzzy Clustering, Evolutionary Algorithms, Evolutionary Clustering, Applications.

WEB PAGE: LINK

In collaboration with:
dibris
sig-l
IEEE Italy Section Computational Intelligence Society
              Chapter LOGO
siren
shro


Additional Info

Venue:  Classes will take place at the Department of Informatics Bioengineering Robotics and Systems Engineering (DIBRIS) of the University of Genova in Via Dodecaneso 35, 16146 Genova. See here for directions and traveling information.

Genova is in the region of Liguria in the Italian Riviera (see here or here for some nice pics and a video).

Credits and Exams: If you attend most of the classes you will be attributed 6 credits with the DIBRIS metric (or 2 credits according to the ECTS grading scale). The credits attribution will be reported on the certificate of attendance we will handle at the end of the course.

If you need an evaluation, the exam will consist in a sw project or in a seminar.

Prerequisites: Calculus, Linear Algebra, Statistics