PhD Summer Course - Machine Learning: A Computational Intelligence Approach, 4-7 June 2018, Italy


Deadline:

May 28, 2018

Event Date:

June 04, 2018 - June 07, 2018


Opportunity Cover Image - PhD Summer Course - Machine Learning: A Computational Intelligence Approach, 4-7 June 2018, Italy

PhD-Summer Course - Machine Learning: A Computational Intelligence Approach 4-7 June 2018, Italy

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. Some applications of Computational Intelligence methods to supervised and unsupervised problems of Machine Learning are presented in the course.

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. Genova is in the region of Liguria in the Italian Riviera.

Credits and Exams 

If the participant attends most of the classes he/she 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 will be handled at the end of the course. If the participant need an evaluation, the exam will consist in a sw project or in a seminar.

Prerequisites 

Calculus, Linear Algebra, Statistics

Period

Jun 4-7, 2018 (Mon-Wed 10:00 am - 13.00 pm,  2:00 pm - 6:00 pm; Thu 10:00 am - 13.30 pm  only)        
Number of hours: 18 (+some students' seminars)  

Instructors

Francesco Masull DIBRIS - UniGe (email: francesco.masulli@unige.it)

Stefano Rovetta DIBRIS - UniGe (email: stefano.rovetta@unige.it)

Syllabus

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

For more information click "LINK TO ORIGINAL" below.

 



Host Country
Study Levels
Publish Date
March 12, 2018
Link To Original




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