Universitat Politècnica de Catalunya · BarcelonaTech

Machine Learning and Models for Decision Making (250443) – Course 2024/25 PDF

Contents

Elements in a decision making scheme: Decision Maker, Actions, Random States, Utility, Optimization Criteria. A priori schemes. A posteriori schemes. Probabilistic description of an experiment. Bayes' updating. Pre-posterior schemes. Applications of decision schemes.

Dedication

6h Large group + 3h Laboratory classes + 12h 36m Self Study
Total: 21h 36m

Algebraic SVD Principal Components Analysis (PCA) and Karhunen-Loève theorem Multidimensional Scaling (MDS) Nonlinear dimensionality reduction

Dedication

3h Large group + 6h Medium group + 3h Laboratory classes + 16h 47m Self Study
Total: 28h 47m

Monte-Carlo sampling and Stochastic FEM Reduced order modeling

Dedication

3h Large group + 3h Laboratory classes + 8h 23m Self Study
Total: 14h 23m

Introduction to machine learning Feed-forward netwok mappings. Network training. Error Backpropagation. Error Functions. Learning and regularization. Artificial Neural Networks for regression and classification

Dedication

3h Large group + 3h Medium group + 3h Laboratory classes + 12h 36m Self Study
Total: 21h 36m

Dedication

3h Laboratory classes + 4h 11m Self Study
Total: 7h 11m