Deep Learning Neural Networks

Caracterização geral

Pré-requisitos

Introduction to deep learning
History and cognitive basis of neural computation.
The perceptron / multi-layer perceptron
The neural net as a universal approximator
Optimization by gradient descent
Back propagation Overfitting and regularization (Dropout)
Convolutional Neural Networks (CNNs)
Training with shared parameters: the convlutional model Recurrent Neural Networks (RNNs)
Exploding/vanishing gradients Long Short-Term Memory Units (LSTMs)

Bibliografia

Deep Learning. Ian Goodfellow, Yoshua Bengio, Aaron Courville. MIT Press, 2016.

Método de ensino

First epoch: deep learning project.

Second epoch: deep learning project

Método de avaliação

English

Conteúdo

Theoretical and practical classes.

Cursos

Cursos onde a unidade curricular é leccionada: