Machine Learning
The aim of machine learning is the development of theories, techniques and algorithms to allow a computer system to modify its behavior in a given environment through inductive inference. The goal is to infer practical solutions to difficult problems --for which a direct approach is not feasible-- based on observed data about a phenomenon or process. Machine learning is a meeting point of different disciplines: statistics, optimization and algorithmics, among others.
The course is divided into conceptual parts, corresponding to several kinds of fundamental tasks: supervised learning (classification and regression), unsupervised learning (clustering, density estimation) and semi-supervised learning (reinforcement). Specific modelling techniques studied include artificial neural networks and support vector machines. An additional goal is getting acquainted with R, a powerful computing environment based on free software.