180 Coding Experiments in 180 Days
Write Code for Machine Learning Every Day
I create a project called 180 coding experiments in 180 days in my GitHub.
Recently, I really feel that my poor programming skills seriously limit my machine learning experiments and understandings. For example, I've been struggling with the code of
Spearmint for the last several months, but without too much improvement.
Then I started from easier ones such as the code in Machine Learning: An Algorithmic Perspective, which makes me feel good. By following through the code flows, it is easier to understand some deep concepts in machine learning. I now believe that writing and reading code is essential to grasping the ideas of machine learning algorithms.
Code as habit
Inspired by the post by John Resig, I decide to set several rules:
- I must write code every day. I can read books, or write blog posts, or other things but it must be in addition to the code that I write.
- It must be useful code. No tweaking indentation, no code re-formatting, and if at all possible no refactoring. (All these things are permitted, but not as the exclusive work of the day.)
- The code must be in GitHub, preferably in the form of IPython Notebook.