https://github.com/spectureram/movie-recommendation-system
A Python-based application that recommends movies based on a user's input. Built with Streamlit, the system uses collaborative filtering and content-based techniques to suggest similar movies. Simply enter a movie title, and the system will generate a list of top recommendations tailored to your preferences.
https://github.com/spectureram/movie-recommendation-system
huggingface pandas python
Last synced: 4 months ago
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A Python-based application that recommends movies based on a user's input. Built with Streamlit, the system uses collaborative filtering and content-based techniques to suggest similar movies. Simply enter a movie title, and the system will generate a list of top recommendations tailored to your preferences.
- Host: GitHub
- URL: https://github.com/spectureram/movie-recommendation-system
- Owner: SpectureRam
- License: mit
- Created: 2024-08-25T07:43:49.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-27T04:44:30.000Z (9 months ago)
- Last Synced: 2024-08-27T05:39:39.634Z (9 months ago)
- Topics: huggingface, pandas, python
- Language: Python
- Homepage: https://huggingface.co/spaces/sairamn/movie-recommendation-system
- Size: 4.88 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Movie Recommendation System
This project is a **Movie Recommendation System** built using Python, Streamlit, and various machine learning techniques. The system recommends movies to users based on a selected movie title by analyzing movie titles, genres, and user ratings. The project utilizes data from the **MovieLens** dataset.
## Features
- **Interactive Web Interface**: Built with Streamlit for a user-friendly experience.
- **Movie Search**: Search for a movie by title to get personalized recommendations.
- **Similar Movie Recommendations**: Provides a list of movies similar to the one searched based on user ratings and movie content.
## How It Works
1. **Data Loading**: Downloads and loads the `movies.csv` and `ratings.csv` files from Google Drive if they are not already present.
2. **Movie Search**: The user inputs a movie title, which is cleaned and vectorized. The system then finds movies with similar titles.
3. **Recommendation Engine**: For the selected movie, the system identifies similar movies based on user ratings using collaborative filtering techniques.
## Installation
Follow these steps to set up and run the project locally:
1. **Clone the repository**:
```bash
git clone https://github.com/yourusername/movie-recommendation-system.git
cd movie-recommendation-system
```
2. **Install dependencies**:
```bash
pip install -r requirements.txt
```
3. **Run the application**:
```bash
streamlit run app.py
```
4. **Data Files**:
The `movies.csv` and `ratings.csv` files are automatically downloaded from Google Drive using the `gdown` library if they do not already exist in the project directory.
## Usage
1. Run the application using `streamlit run app.py`.
2. Open your web browser and navigate to `http://localhost:8501`.
3. Enter a movie title in the text input box (e.g., "Toy Story").
4. View the list of recommended movies based on the selected movie.
## Dependencies
- Python 3.7+
- Streamlit (`streamlit`)
- Pandas (`pandas`)
- Scikit-learn (`scikit-learn`)
- gdown (`gdown`)
- NumPy (`numpy`)
## Example
Search for a movie like "Toy Story," and the system will display top recommendations based on similar user preferences and movie characteristics.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
## Contributing
Contributions are welcome! Feel free to submit a pull request or open an issue for any suggestions or improvements.
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