In the Beginning, there was Research
Updated: Oct 16, 2019
Research for the book is in full swing. These are five sources going into my research.
1. Real-World Machine Learning by Henrik Brink, Joseph W. Richards, and Mark Fetherolf
A good overview book of the process and steps to consider when building a model. It does not go too heavily into the theory or coding and focuses more on process and high-level overview. For me it is a great refresher as I dive into the next sources.
2. Machine Learning by Tom Mitchell
Originally published over twenty years ago (1997) it is also an overview introduction book but with a focus on the algorithms. This book was recommended to me by a college and friend with praise for the mathematical aspects of book, but also with a warning for the mathematical aspects of the book (it can get rather dry and like a text book).
I first took this course nearly 18 months ago and really enjoyed it. It has a nice cadence between intro to the algorithm, coding in Python or R (both are given), and using example data. You can follow along and type out the code (preferred to grow your comfort) while the full templates are available for download.
Developer Education Site
4. Machine Learning Mastery by Jason Brownlee PhD
This site recently came up during online searches and I have yet to fully dive in. However, the overview information and associated books look to be right on par with getting users started and comfortable with the process. I will be using this as a reference as I write as well as occasionally checking for new content.
Bonus - Research Papers!
5. arXiv.org from Cornell University
Want to find your next thrilling read by searching published academic research papers in particular specialized fields!?!? Well arXiv is for you!
In all seriousness, it is cool to search sites like arXiv and find what academics is doing. It can quickly lead down a rabbit hole, as when I first found this site I printed out one paper (The Anatomy of American Football by Konstantinos Pelechrinis and Evangelos Papalexakis) then immediately searched for one of its references (Predicting Margin of Victory in NFL Games by Jim Warner) and during that search found another interesting paper (The Performance of Betting Lines for Predicting the Outcome of NFL Games by Greg Szalkowski and Michael L. Nelson).