- Visualizing What Convnets Learn
- Visualizing the Loss Landscape of a Neural Network
- Getting Started with TPUs on Kaggle
- Six Varieties of Gaussian Discriminant Analysis
- Optimal Decision Boundaries
- Least Squares with the Moore-Penrose Inverse
- Understanding Eigenvalues and Singular Values
- Visualizing Linear Transformations
- What I'm Reading 1: Bayes and Means
- investmentsim - an R Package for Simulating Investment Portfolios

- Visualizing What Convnets Learn - January 9, 2021
- Visualizing the Loss Landscape of a Neural Network - December 30, 2020
- Getting Started with TPUs on Kaggle - July 10, 2020
- Six Varieties of Gaussian Discriminant Analysis - April 19, 2020
- Optimal Decision Boundaries - January 9, 2020
- Least Squares with the Moore-Penrose Inverse - November 21, 2019
- Understanding Eigenvalues and Singular Values - November 15, 2019
- Visualizing Linear Transformations - November 12, 2019
- What I'm Reading 1: Bayes and Means - October 4, 2019
- investmentsim - an R Package for Simulating Investment Portfolios - September 11, 2019
- Talk: An Introduction to Categories with Haskell and Databases - June 22, 2019
- A Somewhat Better Retirement Formula - May 15, 2019
- Journal Review: Permitted and Forbidden Sets in STLNs - April 8, 2019
- Change of Basis for Vectors and Covectors - March 18, 2019
- A Tour of Tensors - February 5, 2019
- Bayesian Topic Modeling - January 30, 2019