Neural Networks and Deep Learning

3 Credits

Nonlinear modeling and neural networks. Gradient descent learning in the additive neural model; statistical learning concepts; dynamic neural networks, function approximation and short-term memory; unsupervised learning networks; generative models and statistical representation; autonomous learning using cognitive principles. Importance and challenges of deep learning; applications for image, video, speech recognition.