|
Mutua da
|
20810262 Deep Learning in Ingegneria informatica LM-32 GASPARETTI FABIO
(programma)
Introduzione al Deep Learning; Addestramento di architetture Deep: tecniche di hyperparameter tuning, batch normalization, faster optimizers, regularization per reti deep; Convolutional Neural Networks (CNN/ConvNets); Analisi di sequenze: Recurrent Neural Networks (GRU, LSTM, Bidirectional); Architetture Encoder-Decoder, Autoencoders, Variational Autoencoders; Attention layers ; Generative Adversarial Networks (GAN); Deep Reinforcement Learning; Embeddings; Principali architetture convolutive (AlexNet, VGG, NiN, GoogLeNet/Inception, ResNet, DenseNet); Applicazioni alla Computer Vision e all'Analisi del linguaggio naturale in linguaggio Keras.
(testi)
Simon J.D. Prince. "Understanding Deep Learning". MIT Press Dec 5th 2023 A. Geron,
“Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems”, O'Reilly Media, Inc, USA, 2019.
|
Università Roma Tre