Mutual Information

Jensen's Inequality

Bellman Equations, Dynamic Programming, Generalized Policy Iteration | Reinforcement Learning Part 2

Jensen's Inequality

The Kelly Criterion

Linear Regression in 12 minutes

The Most Important (and Surprising) Result from Information Theory

Importance Sampling

The Principle of Maximum Entropy

The Bernstein Basis

The Bias Variance Trade-Off

What happens at the Boundary of Computation?

Temporal Difference Learning (including Q-Learning) | Reinforcement Learning Part 4

How to Learn Probability Distributions

Factor Analysis and Probabilistic PCA

The Exponential Family (Part 2)

The Exponential Family (Part 1)

Policy Gradient Methods | Reinforcement Learning Part 6

The Boundary of Computation

Reinforcement Learning, by the Book

Why Do Tree Based-Models Outperform Neural Nets on Tabular Data?

The Fisher Information

Why Do Neural Networks Love the Softmax?

Monte Carlo And Off-Policy Methods | Reinforcement Learning Part 3

Is the Future of Linear Algebra.. Random?

Function Approximation | Reinforcement Learning Part 5