I have been working through the Python Crash Course book by Eric Matthes. I got to Chapter 17, Working With API’s  and ran the example code python_repos_updated.py that generates an SVG graph of the most starred Github Python projects. The thing that stands out to me is the amount of machine learning related resources that show up on this hot list. The interactive graph is generated by using Pygal which works well and is easy to use.

Interactive SVG Graph of Most Starred Github Python Projects

Out of curiosity I looked at the most starred C projects on Github as well with a simple modification of the code.

Interactive SVG Graph of the Most Starred Github C Projects

Python Crash Course

The book has been a good resource to develop programming skills in Python, my background is in C primarily and this book was an excellent starting point to officially learn Python. What I mean by that, is that I have been using Python by modding other peoples code when I need some piece of code to use for some application. For a few years I was learning it that way on an as needed basis (plus using the Internet to look up things that I might get suck on) which works to a point. When I started to get into machine learning a bit deeper, I could see that having a more formal introduction to Python would be helpful. Having a book that goes through the process formally helped to quickly build skills in my opinion. In a matter of a few months I have gone through a decent amount of the book and have been able to branch off some of the examples and create free standing code that was interesting to learn from.