Mathematics

Scaling Laws

Approximation Theory

Lecture 3: Dominance

Generative Models: Basics

PyTorch Tutorial

Hacker's Guide to Deep Learning

Bayesian Nash Equilibrium: Applications

Deep Learning for Natural Language: Transformers

Lecture 22: Signaling

Generalization: Out-of-Distribution (OOD)

Introduction to Neural Networks and Deep Learning; Training Deep NNs

Options Markets

Transfer Learning: Data

Lecture 20: Ad Auctions

Metrized Deep Learning

Deep Learning for Natural Language: The Basics

Lecture 14: Folk Theorem

Scaling Rules for Optimization

Representation of Games

From Guinness to Clinical Trials: The Story of T-Distribution

Deep Learning for Natural Language: Embeddings

Transfer Learning: Models

Lec 11: Representation Learning: Reconstruction-Based

How to Train a Neural Net