Deep Learning

The emphasis of the course is on practical applications of deep learning. We learn how to use TensorFlow 2.0 and Keras for the creation of convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory networks (LSTMs), autoencoders, generative adversarial networks (GANs), and transformers with attention.