Major Project in Machine Learning under Professor Richa Singh
Using Movielens dataset developed a personalized movie recommendation system
Dataset consists of movies.csv and ratings.csv
Very huge dataset of approximately 2 crore 30 lakhs ratings
Collaborated on preprocessing and analysis of movies for accurate and relevant recommendations
Implemented machine learning algorithms like K-Means, KNN and Cosaine Similarity
Finally recommended top 20 movies based on the movie given by the user
The purpose of a recommendation system basically is to search for content that would be interesting to an individual. Recommendation systems are Artificial Intelligence based algorithms that skim through all possible options and create a customized list of items that are interesting and relevant to an individual. These results are based on their profile, search/browsing history, what other people with similar traits/demographics are watching, and how likely you are to watch those movies. Your aim will be to recommend similar movies if a type of movie is given.