Curso:
Pós-Graduação em Data Science for Finance
Unidade curricular:
Machine Learning in Finance
Semestre:
Primavera
Número de créditos:
7,5
Número de horas de aula por semana:
2
Objetivos da unidade curricular:
- Understand the design principles of neural networks;
- Understand the concept of activation function;
- Understand the backpropagation algorithm for training a neural network;
- Being able to build a neural network to solve classification tasks;
- Being able to use Keras or similar libraries to build a Neural Network;
- Understand the convolution operator and the idea behind convolutional neural network;
- Understand the main principles of recurrent neural network;
- Understand LSTM and how they can be applied to counteract vanishing gradient problem.
- Being able to apply one of the deep model presented to solve financial classification or regression tasks.
Requisitos de frequência:
Língua de ensino:
Português. Em caso de existirem alunos ou professores estrangeiros, as aulas serão dadas em Inglês.