Implemented Collaborative filtering algorithm from scratch for movie recommender system
In this exercise, I implemented collaborative filtering from scratch to build a recommender system for movies
- ex8_cofi.m - Octave/MATLAB script for second part of exercise
- ex8_movies.mat - Movie Review Dataset
- ex8_movieParams.mat - Parameters provided for debugging
- checkCostFunction.m - Gradient checking for collaborative filtering
- computeNumericalGradient.m - Numerically compute gradients
- fmincg.m - Function minimization routine (similar to fminunc)
- loadMovieList.m - Loads the list of movies into a cell-array
- movie ids.txt - List of movies
- normalizeRatings.m - Mean normalization for collaborative filtering
- cofiCostFunc.m - Implement the cost function for collaborative filtering
Submited to and evaluated by Machine Learning Coursera course as Stanford