This course (CS229) -- taught by Professor Andrew Ng -- provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed. - Kenny Sanders
At its best, computer science is an exciting blend of programming, mathematics, and problem solving. This course will introduce an interesting variety of subjects in programming, algorithms, and discrete mathematics though puzzles and problems which have appeared in the International ACM Programming Contest and similar venue - Kenny Sanders
Many programming languages come with a REPL (read-eval-print loop), which allows you to type in code line by line and see what it does. This is quite useful for prototyping, experimentation, and debugging code. Other programming languages, and especially C, use a "compile-run" model, and don't provide a REPL. Let's fix that. - Kenny Sanders
This library implements something which is often called live coding or code reloading. It allows an application to have any Python code which might be part of it updated as the files the code is in are changed - while the application is running. - Kenny Sanders
