What I cannot build. I do not understand. — Richard Feyman
This repository is mainly served as an education purpose. It contains my implementation of classical computer science concepts, including algorithms and data structures.
Well, it’s not a standard term (don’t look for it on Google). It’s just my personal term for classifying some categories in my learning list. It’s inspired from Classical Physics (e.g. Newton) and Modern Physics (e.g. Einstein, quantum physics).
In analogy, classical computer science consists of the *Topics below (will be gradually updated followed my implementation). Modern computer science consist of machine learning, deep learning, general AI stuffs (which I hope I will find time to implement soon). Well, of course some techniques of machine learning or general AI already exists pre-2000 but let’s categorize them following the trend.
Most algorithms and data structures are implemented in C, Python or Java.
If I have implementations in multiple languages, they are divided into two corresponding directories c, python or java.
- Usually implementations are tested with
pytest, directly in the files. - To test:
pytest <implementation.py>