Presentations and Archive

AI Presentations

• Andromeda Presentation
• Andromeda Presentation Git
• Coding Agents for Historical Research

Linear Algebra

Here are some notes on linear algebra for econometrics and machine learning:

1. Interpretations of matrix multiplication
2. Change of basis and a change of perspective
3. Visualizing linear projection
4. Orthogonal bases, Gram–Schmidt, and QR decomposition
5. Rank-nullity in a regression context
6. Singular value decomposition
7. Matrix calculus
8. Norms, distances, and similarity
9. Covariance, positive semidefinite matrices, and distance
10. Hyperplanes, distances, and margins
11. Constrained optimization, duality, and support vector machines

Other Courses

Here is some course material of courses I’ve taught in the past:

• Big Data, Big Questions: An introduction to Excel and Data Science for historians (2017).