Deep Learning Neural Networks
Objectives
NA
General characterization
Code
200206
Credits
4.0
Responsible teacher
Mauro Castelli
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
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)
Bibliography
Deep Learning. Ian Goodfellow, Yoshua Bengio, Aaron Courville. MIT Press, 2016.
Teaching method
First epoch: deep learning project.
Second epoch: deep learning project
Evaluation method
English
Subject matter
Theoretical and practical classes.