CAMINHA, V. L.; http://lattes.cnpq.br/2172825162678603; CAMINHA, Vítor Leão.
Resumo:
Due to the recent development of the area of deep learning in the field of artificial
intelligence, many theoretical and practical concepts are still obscure and with little
documentation for beginning researchers in the area. In this context, this undergraduate
thesis aims to explain some basic concepts and their influences on the performance
and results of deep learning systems and neural networks. In addition to the theory, didactic
experiments were implemented to exemplify practical constructions of systems
with different architectures, for different problems, comparing the activation functions,
optimization and regularization algorithms, initial parameter values, among others, optimizing
the networks with better design choices for the specific problems.