Università degli Studi di Trieste · Dipartimento di Fisica · tutti i canali con docenti e libri, a.a. 2026/2027
Docente non ancora indicato Canale unico
Corso di laurea: Fisica – sede di Trieste, Sede di Trieste · Laurea magistrale (LM-17) · esame facoltativo · Scienze e Tecnologie Quantistiche / 1º anno · 2º semestre · Scienze e Tecnologie Quantistiche · 6 CFU
Argomenti del programma: The course provides an extensive treatment of deep learning starting from the basics to advanced topics. - Introduction to deep learning - Artificial neurons, shallow networks, deep networks - Loss functions - Gradient descent and its variants - Backpropagation - Regularization - Convolutional neural networks - Recurrent neural networks - Attention models and transformers - Introduction to deep unsupervised learning…
Corso di laurea: Mathematics – sede di Trieste · Laurea magistrale (LM-40) · 2º anno · 2º semestre · 6 CFU / 1º anno · 2º semestre · Computational Mathematics and Modelling · 6 CFU
Argomenti del programma: The course provides an extensive treatment of deep learning starting from the basics to advanced topics. - Introduction to deep learning - Artificial neurons, shallow networks, deep networks - Loss functions - Gradient descent and its variants - Backpropagation - Regularization - Convolutional neural networks - Recurrent neural networks - Attention models and transformers - Introduction to deep unsupervised learning…
Argomenti del programma: The course provides an extensive treatment of deep learning starting from the basics to advanced topics. - Introduction to deep learning - Artificial neurons, shallow networks, deep networks - Loss functions - Gradient descent and its variants - Backpropagation - Regularization - Convolutional neural networks - Recurrent neural networks - Attention models and transformers - Introduction to deep unsupervised learning…
Libri Universitari