A content-based movie recommendation system built with Python, NumPy, and Pandas, utilizing the MovieLens dataset to suggest films based on genre similarity and user preferences.
This project implements a foundational movie recommendation system using content-based filtering. By analyzing movie genres and user interactions from the MovieLens dataset, the system identifies films similar to those a user has enjoyed, providing personalized suggestions. It demonstrates practical data manipulation and basic machine learning concepts with Python.
- Content-Based Filtering: Recommends movies by finding similarities in genre and attributes.
- MovieLens Dataset Integration: Uses the popular MovieLens dataset for comprehensive movie and rating information.
- Genre Similarity Calculation: Determines how similar movies are based on their genre tags.
- Data Processing with Pandas: Efficiently loads, cleans, and manipulates large datasets.
- Numerical Operations with NumPy: Performs high-performance array computations for similarity metrics.
- User Preference Analysis: Adapts recommendations based on a user's perceived interests.
Core Technologies:
Dataset:
- Python 3.x: Download here
- pip: Comes with Python
- Clone the repository
git clone https://github.com/AnishCoder2006/Movie-Recommendation-System-Using-Numpy-and-Pandas-with-MovieLens-Dataset.git cd Movie-Recommendation-System-Using-Numpy-and-Pandas-with-MovieLens-Dataset
2.Install dependencies
bash pip install numpy pandas (Optional: create a requirements.txt with numpy and pandas and run pip install -r requirements.txt.)
3.Download the MovieLens Dataset
Get the MovieLens 1M Dataset.
Unzip into a data/ directory in the project root.
Project structure:
Code Movie-Recommendation-System-Using-Numpy-and-Pandas-with-MovieLens-Dataset/ ├── data/ │ ├── movies.dat │ ├── ratings.dat │ └── users.dat ├── recommendationSystem.py └── README.md Usage Run the recommendation system:
bash python recommendationSystem.py The script loads the dataset, processes it, and prints recommendations to the console. Check recommendationSystem.py for how to input a specific movie or adjust configuration.
📁 Project Structure Code Movie-Recommendation-System-Using-Numpy-and-Pandas-with-MovieLens-Dataset/ ├── data/ # MovieLens dataset files ├── recommendationSystem.py # Core recommendation logic └── README.md # Documentation 🤝 Contributing Contributions are welcome!
Fork the repository
Create a new branch (git checkout -b feature/your-feature-name)
Commit changes (git commit -am 'feat: Add new feature')
Push (git push origin feature/your-feature-name)
Open a Pull Request
📄 License This project currently has no explicit license. Consider adding one (MIT, Apache 2.0, etc.) for clarity.
🙏 Acknowledgments MovieLens Dataset: Provided by GroupLens Research at the University of Minnesota.
⭐ Star this repo if you find it helpful!
Made with ❤️ by AnishCoder2006
