Content-Based Movie Recommendation System :
This project implements a content-based movie recommendation system using the TMDB Movies dataset from Kaggle. The dataset contains information about 45,000 movies, including cast, crew, plot keywords, budget, revenue, and more.
Overview:
The recommendation system works by analyzing the content of a movie (e.g., genres, actors, directors, keywords) and recommending similar movies to the user. This can be helpful for users who are looking for movies that they are likely to enjoy based on their past preferences.
Dataset:
The TMDB Movies dataset used in this project can be found on Kaggle: https://www.kaggle.com/datasets/rounakbanik/the-movies-dataset/data
Dependencies:
This project requires the following Python libraries:
pandas, numpy, scikit-learn.