The course will present artificial intelligence techniques for extracting usefull knowledge from data. More specifically, the course will introduce in details concepts such as Optimization and machine Learning and it will focus on stochastic heuristic methods like, among the others, Genetic Algorithms, Particle Swarm Optimization and Neural Networks.
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Machine Learning. Tom Mitchell; Genetic programming: on the programming of computers by means of natural selection. J. Koza; 0; 0; 0
Classes are partitioned into theoetical classes and practical classes.
Theoretical classes will be held using the board and slides.
In the practical classes students will implement the algorithms presented in the theoretical classes.
First epoch: project (30%) and oral exam (70%)
Optimization problems: definition of problem and instance of a problem
Search space, neighborhood structure and related concept
No free lunch theorem
Semantic genetic programming
Multi objective optimization (NSGA II)
Classification and clustering
Performance of a Classifier
Generalization and overfitting
Artificial Neural Networks