Recommendation-system

Creating recommendation system with #project-of-the-week in DataTalks.Club

Part of Datatalks clubs and Alexey Grigorev's project of the week! Recommendation system based on content based filtering and collaborative based filtering

Project 1 - Content based Movie recommendation from kaggle dataset

This is content based movie recommendation system by filtering the titles based on overview column from the Kaggle dataset using TfidfVectorizer and Cosine simularity

Dataset: "https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata

Reference taken from: https://www.youtube.com/watch?v=ijtxuF_5kEU

Project 2 - Content based Movie recommendation system

This is content based movie recommendation system by filtering the titles based on title column from the dataset. Changed the movie title name to be easily used by ML using regular expression (or RE) and created the model using TfidfVectorizer and Cosine simularity

Dataset: https://files.grouplens.org/datasets/movielens/ml-25m.zip

Reference taken from: https://www.youtube.com/watch?v=eyEabQRBMQA

Project 3 - Collaborative based Movie recommendation system

This is collaborative based movie recommendation system by filtering the titles based on ratings given by users and movies watched/liked by users from the dataset. Created using pivot table and Cosine simularity. Also we have found top 50 popular movies from the dataset.

Dataset: https://files.grouplens.org/datasets/movielens/ml-25m.zip

Reference taken from: https://www.youtube.com/watch?v=1YoD0fg3_EM&t=2908s