The Math of AI (Course 2): Deep Learning
DEEP LEARNING: This course (2 of 2) provides a rigorous in-depth coverage of the mathematics of Deep Learning. It starts with neural network basics. Next it delves into deep reinforcement learning, covering Monte Carlo Tree Search, AlphaGo, AlphaZero, and Alpha Tensor. Next it covers Generative AI, in particular, Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models. Finally, it covers generative language models including Word2Vec, Attention Mechanism, Transformer, Large Language Models (LLMs), and Contrastive Language Image Pretraining (CLIP).
Course•By Stephen Odaibo
