Fundamentals Of Artificial Intelligence, Machine And Deep Learning – Politecnico di Torino

• Copies of the slides used during the lectures will be made available. All teaching material is downloadable from the teaching Portal.
• K. P. Murphy. Machine Learning: a probabilistic perspective. MIT Press

Argomenti del programma: - Artificial Intelligence: historical definition, brief overview, modern definition and current role of machine and deep learning. - Overview of fundamental knowledge of probability. - Generative and discriminative methods. - Perceptron. - Artificial Neural Networks. - Support Vector Machines. - Kernel functions. - Active learning - Convolutional Neural Networks. - Stochastic Gradiant Descent. - Batch Normalization.