Why Do Neural Networks Love the Softmax?

Is the Future of Linear Algebra.. Random?

The Most Important (and Surprising) Result from Information Theory

What happens at the Boundary of Computation?

The Boundary of Computation

Why Do Neural Networks Love the Softmax?

Policy Gradient Methods | Reinforcement Learning Part 6

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

Function Approximation | Reinforcement Learning Part 5

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

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

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

Reinforcement Learning, by the Book

The Kelly Criterion

Importance Sampling

Factor Analysis and Probabilistic PCA

The Exponential Family (Part 2)

Gaussian Processes

The Exponential Family (Part 1)

The Principle of Maximum Entropy

The Bernstein Basis

Linear Regression in 12 minutes

The Fisher Information

How to Learn Probability Distributions

The Bias Variance Trade-Off