Items on this page will be added as I complete them. First I have to write a bunch of pages related to numerical analysis - then I'll be focused on writing tools for mathematics-intensive data analysis.

- I help organize a few Data Science and Machine Learning meetup groups in Boulder and Longmont, Colorado. The "Boulder Data Science Machine Learning Course Group" is collectively doing Andrew Ng's ML course (see below). Since I already took the course for a certificate I am going to do a few different things: (1) Implement every ML algorithm in Python in the most general way I can, and (2) write code to help group members understand the core concepts. My code will be posted here as I complete it.
- Week 1: Linear Regression with Gradient Descent. I wrote a pretty cool way to see what happens when the learning rate \( \alpha \) is changed. {Posted 11/16/2016}

- This is an excellent Machine Learning course offered by Dr. Andrew Ng from Stanford University: Certificate

Here are my notes: - Week 1 Notes.
- Week 2 Notes.
- Week 3 Notes.
- Week 4 Notes.
- Week 5 Notes.
- Week 6 Notes.
- Week 7 Notes.
- Week 8 Notes.
- Week 9 Notes.
- Week 10 Notes.
- Week 11 Notes.
- My paper from my MS. (Reprinted with permission from Washington State University Department of Mathematics.) This is a small part of reserach performed by Dr. Kevin Cooper, Dr. Alexander Panchenko at WSU. Paper and Presentation {Posted 7/24/2016} The problem written about here is a nonlinear particle physics problem that used to need a supercomputer cluster to solve. However, with the techniques we developed we can run the same problem on a laptop in a few minutes using Matlab. Groovy.
- I completed a Machine Learning course from the University of Washington Machine Learning Certificate.{Posted 7/4/2016}
- Some notes on 'Classification systems'.{Posted 6/27/2016}
- I finished a fun "R Programming" course from Johns Hopkins University. R Programming Certificate.{Posted 5/31/2016}
- Some notes about simulation and profiling in R {Posted 6/21/2016}
- Some notes about loop functions in R {Posted 6/21/2016}
- Another R Markdown example using data from http://www.eia.gov {Posted 1/10/2016}
- R Markdown (example) {Posted 12/28/2015}
- Least Squares Polynomial Fitting with Matlab {Posted 11/10/2015}
- Least Squares Polynomial Fitting in R {Posted 11/30/2015}
- Numerical analysis for an advection PDE {Posted 11/1/2015}
- Eigenvalues of Graph Adjacency Matrices {Posted 10/25/2015}
- A presentation on the Reproduction Number \(R_0 \) {Posted 10/24/2015} (PDF Opens in new window)