Students who successfully complete this course unit will be able to:

1. To know the theorical foundations of several machine learning techniques, and to be able to implement and apply them to concrete problems.
2. To understand how supervised classification and regression algorithms work and to know how to train and evaluate these algorithms.
3. To understand how unsupervised clustering and dimension reduction algorithms work and to know how to apply them.
4. To know how to combine or modify key elements of machine learning techniques to design new algorithms.
5. To be able to choose the appropriate methods for new problems, and to evaluate their performances.

Curricular Unit Form