This project is aimed at developing a movie recommendation system using Python. The system analyzes movie ratings data to provide personalized movie recommendations to users.
The Movie Recommender System uses a dataset of movie ratings. It performs data analysis and visualization to understand the distribution of ratings and identify popular movies. The system then uses this information to recommend movies that a user might enjoy based on their past viewing history and ratings.
- Data Analysis: The system analyzes movie ratings to calculate the average rating and the number of ratings for each movie.
- Data Visualization: The system visualizes the distribution of ratings and the number of ratings using histograms and jointplots.
- Recommendation: The system recommends movies to users based on their past viewing history and ratings.
Before running the scripts, you need to install the necessary Python libraries. You can do this by running the following command:
pip install pandas matplotlib seaborn IPythonThis will install the following libraries:
- pandas: A library providing high-performance, easy-to-use data structures and data analysis tools.
- matplotlib: A library for creating static, animated, and interactive visualizations in Python.
- seaborn: A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
- IPython: An interactive command-line terminal for Python.
The Movie Recommender System is implemented as a series of Python scripts. To use the system, run the main script and follow the prompts to rate movies and receive recommendations.