Publications
I focus on clear declaration of variables and documentation of equations/algorithms, e.g., full derivations and proofs, not found elsewhere in the literature.
Book Resources
This folder contains the code and a free chapter preview for each of my books, including:
- Machine Learning: a Conceptual Approach.
- Math Refresher for AI & Machine Learning (1st and 2nd editions).
- Math Handbook for AI & Machine Learning (1st and 2nd editions).
- How to do Research, Remotely!
- Optimal Nonlinear Bayesian Estimation and Sensor Fusion.
- The Absolute Beginners Guide to Neural Networks.
Technical Notes
This folder is a collection of technical reference notes on various subjects, e.g., Navigation, Math, Machine Learning, etc. For example Algebra has a list of commonly used algebra equations that most folks learned in high school (and likely forgot), with a section of common algebra mistakes (so that you don’t repeat the mistakes).
Technical Papers
This folder contains most of the journal papers, conference papers, and technical notes that I have published. The topics range from computational fluid dynamics (CFD), aircraft design, autopilot design, GPS-INS (“SatNav”) and navigation system design, applied mathematics and probability theory.
ML Flow Chart
This great machine learning flow chart will help you decide the right algorithm for your data.
You can view the flow-chart here.