Deep Learning

Covers essential topics including deep neural network training optimization, regularization for generalization improvement, convolutional neural networks (CNNs), recurrent and recursive neural networks (RNNs), deep generative models (e.g., GANs, Autoencoders), and transformers with attention mechanisms for various applications including natural language processing.