APPLIED DEEP LEARNING

Catalog description

Explores and applies several neural network architectures, including fully-connected, convolutional, and sequence model based network structures. Topics including gradient descent and optimization, feed forward and back propagation methods, loss functions, activation functions, training, testing, and validation of the networks, as well as other types of advanced networks. Applications including areas such as text sentiment analysis, image classification, and language translation.