I’m interested in learning more about computer programming. Recently, I’ve picked up a book on algorithms and data structures as well as looked into Greenplum and Postgres. I wanted to have a slight change of focus this weekend and picked up Machine Learning in Action over the weekend.
The book has been great so far. It’s written using Python and implements many common machine learning algorithms from scratch. Currently, I’ve gone through 2 chapters, one on KNN and the other on ID3 trees. The later was a bit more challenging then the first, requiring quiet a bit of recursion due to the tree structure involved with that methodology. I like this book so far in that it does a lot of the implementations from scratch, which makes it easier to understand. I still want to get deeper into Shannon entropy and that up to get a better understanding of it.
For those interested in the code behind the book, it can be found here:
https://github.com/pbharrin/machinelearninginaction
Hopefully, I will get to try out the next few chapters. Chapter 4 covers Bayesian methodology.
Best,
Chris
