Machine Learning - complete course notes. The following notes represent a complete, stand alone interpretation of Stanford's machine learning course presented by Professor Andrew Ng and originally posted on the ml-class.org website during the fall 2011 semester.
The topics covered are shown below, although for a more detailed summary see lecture 19. The only content not covered here is the Octave/MATLAB programming. All diagrams are my own or are directly taken from the lectures, full credit to Professor Ng for a truly exceptional lecture course. Intro to AI - Announcements. Carver/pyHTM - GitHub. Solving Every Sudoku Puzzle. By Peter Norvig In this essay I tackle the problem of solving every Sudoku puzzle.
It turns out to be quite easy (about one page of code for the main idea and two pages for embellishments) using two ideas: constraint propagation and search. Sudoku Notation and Preliminary Notions First we have to agree on some notation.