Neural Network Basics
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Neural Networks (Part 1): Linear Regression; Basic NN structure; and a brief history of Deep Learning (35:10)
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Neural Networks (Part 2): Activation functions; Loss functions; Cross-Entropy; and One-hot-encoding (33:25)
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Neural Networks (Part 3): Cross-Entropy Loss Explained; Gradient Descent; and SGD. (24:59)
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Neural Networks (Part 4): Backpropagation; Convolutional Neural Networks. (25:33)
Deep Reinforcement Learning
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Deep Reinforcement Learning Part 1: Intro, Exploration vs Exploitation; Monte Carlo Tree Search (MCTS). (25:29)
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Deep Reinforcement Learning Part 2: Monte Carlo Tree Search (MCTS) example worked out. (24:18)
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Deep Reinforcement Learning Part 3: AlphaGo intro and SL net & roll out net training eqns. (24:20)
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Deep Reinforcement Learning Part 4: more on AlphaGo -- RL net and value net training eqns. (15:45)
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Deep Reinforcement Learning Part 5: AlphaGo Zero (17:19)
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Deep Reinforcement Learning Part 6: Alpha Tensor (27:07)
Generative AI Part 1: GANs, VAEs, and Diffusion Models.
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Generative Adversarial Networks (Part 1): Discriminator vs Generator; Objective function; and KL Divergence. (23:47)
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Generative Adversarial Networks (Part 2): Jensen-Shannon Metric; Analyzing the GAN Objective. (16:14)
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Variational Autoencoders (Part 1): Encoder-Decoder; Reparametrization Trick; Bayesian Inference. (26:07)
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Variational Autoencoders (Part 2): Likelihood Probability; Evidence Lower Bound (ELBO); VAE Objective. (25:07)
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Diffusion Models (Part 1): Forward & Reverse Processes. (17:40)
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Diffusion Models (Part 2): The LeapFrog Property. (23:02)
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Diffusion Models (Part 3): DDPM Objective via KL Divergence of forward and reverse processes. (18:57)
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Diffusion Models (Part 4): Deriving the DDPM Objective (contd). (13:28)
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Diffusion Models (Part 5): Gaussian Forms (21:12)
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Diffusion Models (Part 6): Deriving the Mean and Variance of the Fwd Process Posterior. (22:52)
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Diffusion Models (Part 7): DDPM Loss Function Assuming Fixed Variance. (16:56)
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Diffusion Models (Part 8): DDPM Simple Loss; DDPM Training and Sampling Pseudocodes. (17:40)
Generative AI Part 2: Language Models
