LynnaTian

weekly

Movie-Recommendation-System

Anlyzed and used Movie-Lens dataset of 1 Million users to generate moie recommendations for users to watch, based on movies watched by the user, and the ratings of other users.Popular movies can be found by processing the ratings. Also similar movies are found using cosine similarity measure. Machine Learning Library of Spark MLLib’s Alternating Least Squares recommender system is applied to the data. Another model has also been implemented using Hadoop MapReduce.

recommend_music

recommend music using cosine similarity with collaborative filtering (run in Spark)

test