This course will
give you practical experience with:
·
with both feedforward and
recurrent neural networks,
·
Convolutional neural networks,
·
Recurrent neural networks,
·
Attention and Memory,
·
Autoencoders and Autoregressive
Models,
·
Generative Adversarial
Networks,
·
Variational Autoencoders
·
regularization, dropout, and
normalization to improve generalization.
·
Gradient descent and
backpropagation of loss functions