Machine Learning – Camerino

Argomenti del programma: Intelligenza Artificiale e Machine Learning VC Dimension and Learning Theory Apprendimento Automatico Supervisionato e Non supervisionato Classificazione e Regressione Classificatori: Naive Bayes, k-Nearest Neighbor, Support Vector Machines, Alberi di decisione, Random Forest, Classificatori multi classe, metodi Ensembles Clustering (K-means, EM) e Riduzione di Dimensionalità (PCA, DA) Modellazione di dati…

Argomenti del programma: Supervised and unsupervised learning Regression Models Clustering and classification algorithms Decision Trees, Random Forests Artificial Neural Networks and Learning Methods Artificial Neural Networks architectures and computational paradigm Artificial Neural Networks as universal approximators Algorithms for Artificial Neural Networks training: the back-propagation algorithms and its variants Support Vector…