Other Stuff!

Else

  • When I initially hired on to Denovo Ventures in Boulder Colorado I was an Analytics Engineer.  I was then trained in software engineering.  I really enjoy both roles and would like to find something that relates to both.
  • I am very happy that I have studied math because it is a great foundation for doing a lot of great things in interesting fields like engineering, analysis, and Data Science. After moving back to Colorado from graduate school I started looking for the best thing to do with what I learned in school. It is apparent that Data Science is the "killer app" for mathematicians!
  • If you are looking for an excellent course on Machine Learning, I highly suggest this one. I have my notes and the certificate I earned posted in 'items.' Machine Learning with Andrew Ng (Stanford)
  • I completed this: "Machine Learning" course from University of Washington. Here's a link to the certificate: Certificate
  • I completed this "R Programming" on Coursera from Johns Hopkins University. R Programming Certificate. (Some course notes from this are in "items.")
  • I have countless others that are not as good... But these books are all a good bet:
    1. Fundamentals of Matrix Computations (Watkins, Wiley)
    2. Python Machine Learning (Raschka, Packt)
    3. Mathematical Statistics and Data Analysis (Rice, Duxbury)
    4. An Introduction to Statistical Learning (James, STS)
    5. R In Action (Kabacoff, Manning)
    6. Python For Data Analysis (McKinney, O'Reilly)
    7. R Cookbook (Teetor, O'Reilly)
    8. Practical Data Science with R (Zumel, Manning)
    9. Data Analysis with Open Source Tools (Janert, O'Reilly)
    10. All the Math You Missed (but need to know for graduate school) (Garrity, Cambridge)