Collaborative Filtering Recommendation System

Recommendation systems are widely used in a number of applications to give a personalized user experience. Collaborative filtering uses the information of other users or items in the system to filter out information. A user-based (user-user) collaborative filtering recommendation system is a memory-based approach that utilizes the users’ interactions with the system to find similar users and recommend them the items that similar users have liked.

In this project, we’ll work with an IMDB movie dataset to create a recommendation system for the users using the scikit-learn library, and then we’ll use the Streamlit library to build a simple recommender application.