Facebook Twitter Stanford AI Class Algorithms This is the unofficial code chrestomathy repository for the Stanford Online Introduction to Artificial Intelligence course based on Stanford CS221. The course focuses on machine learning, probabilistic reasoning, robotics, and natural language processing. Implementations of any algorithms learned in the course can be developed in any language and put into this repository. All code submitted to this repository will be available freely, and licensed under the MIT License. clarle/ai-class - GitHub clarle/ai-class - GitHub
Anyone up for implementing the algorithms in actual code? : aiclass Anyone up for implementing the algorithms in actual code? : aiclass So I'm guessing that a whole bunch of us are actual programmers, but the class itself doesn't require any actual programming. I personally learn better when I actually code the algorithms up myself, though, so I was wondering if anyone might be interested in helping me implement the algorithms in class in a whole bunch of languages, a la Rosetta Code. I'm personally strongest in Python/Cython, and I'm fairly familiar with the NumPy/SciPy libraries for linear algebra and probability, so I could definitely write up code there. I'm a capable JavaScript person too, if we wanted to make some fun HTML5 visualizers (and I've always wanted to play around with the glMatrix library!). I'll probably be doing this on my own regardless, but if anyone's interested in helping out in any other language or just improving my code, I'll open up a Github repo today and start implementing the searches in Unit 2 later tonight. Started a GitHub repository, you can find it at