Algoritmos Genéticos e Redes Neuronais

- To understand the way Genetic Algorithms (GA) work as a optimizing method.

- To be able to apply GA to simple problems using some software implementation of GA.

- To understand the neural networks basic types: feedforward, convolution and recurrent.

- To know the different Cost functions. To understand the usual optimization method used in neural networks: gradient descent. To understand the role of the different hyperparameters used in neural networks: number of layers, number of units on each layer and learning rate. To understand the different types of regularization and the situations that require the use of regularization.