Movie-recommendation-system

For capillary hackathon. 18th-27th Aug.

Place proper dataset from movielens in data/.
First run create.py.
Next run learn.m.

Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
.gitignore		.gitignore
README.md		README.md
X_mov_feat.mat		X_mov_feat.mat
Y_matrix1.mat		Y_matrix1.mat
closestCentroids.m		closestCentroids.m
clustering.m		clustering.m
clusters.mat		clusters.mat
cofiCostFunc.m		cofiCostFunc.m
cofiCostFunc1.m		cofiCostFunc1.m
computeCentroids.m		computeCentroids.m
create.py		create.py
disp.py		disp.py
final_movie_ids.mat		final_movie_ids.mat
fmincg.m		fmincg.m
io.m		io.m
learn.m		learn.m
loadMovieList.m		loadMovieList.m
movie_cluster.mat		movie_cluster.mat
movie_ids.txt		movie_ids.txt
normalise.m		normalise.m
normalizeRatings.m		normalizeRatings.m
numbers_users_movies.txt		numbers_users_movies.txt
octave-workspace		octave-workspace
predict.m		predict.m
rec_cost_function.m		rec_cost_function.m
recommend.m		recommend.m
train_MR.m		train_MR.m
user_generator.m		user_generator.m
users.mat		users.mat

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