Generative Models

This course covers the learning outcomes and goals of understanding generative models, including denoising and variational autoencoders, generative adversarial networks (GANs), and restricted Boltzmann machines (RBM). Students will learn the individual skills and tools required to work with these models. The teaching method involves providing a friendly introduction to each topic. The intended audience for this course includes individuals interested in deep learning, machine learning, and artificial intelligence.