Machine Learning And Neural Networks – Politecnico di Torino

Argomenti del programma: Discrete-time random signals and processes, probability distributions, model fitting (1.2CFU), including: • Introduction to machine learning; supervised vs. unsupervised learning, regression vs. classification, k-NN classifier, the curse of dimensionality, overfitting. • Review of probability, continuous vs.