Math for Machines
About Archive

Recent Posts

  • 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
  • Talk: An Introduction to Categories with Haskell and Databases
  • A Somewhat Better Retirement Formula
About

This is the website of Ryan Holbrook. You can contact me at ryan@mathformachines.com.

I currently work at Kaggle as an AI Educator. I am also on Twitter and GitHub.

Tags

bayesian BMA calculator category-theory classification coordinates covectors cql data-science decision-boundaries eigenvalues engrams finance functional-programming generalized-inverse geometry haskell investing julia kaggle LDA least-squares linear-algebra linear-equations matrix-decomposition MCMC memory moore-penrose-inverse neural-networks neuroscience NLP numpy python QDA R ReLUs retirement review sage simulation singular-values stacking talk tensorflow tensors tpus tutorial vectors

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