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https://github.com/ashudevcodes/steam-game-recommendation-system
Creating a Steam game recommender using content-based suggestions, analyzing tags, descriptions, genres. Limited data from 2021-2023, focused on recent releases.
https://github.com/ashudevcodes/steam-game-recommendation-system
recommender-system steam steam-games streamlit-webapp
Last synced: about 1 month ago
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Creating a Steam game recommender using content-based suggestions, analyzing tags, descriptions, genres. Limited data from 2021-2023, focused on recent releases.
- Host: GitHub
- URL: https://github.com/ashudevcodes/steam-game-recommendation-system
- Owner: ashudevcodes
- License: mit
- Created: 2023-08-11T05:41:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-28T15:41:28.000Z (5 months ago)
- Last Synced: 2024-07-28T17:02:45.979Z (5 months ago)
- Topics: recommender-system, steam, steam-games, streamlit-webapp
- Language: Jupyter Notebook
- Homepage: https://huggingface.co/spaces/ashuNicol/Steam-game-Recommendation-System
- Size: 49.3 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Steam Game Recommendation System
https://github.com/user-attachments/assets/ae766122-af48-4b77-937c-17437cfb41a9
This project aims to build a Steam game recommendation system using content-based suggestions. It analyzes game tags, descriptions, and genres to provide personalized recommendations to users. The system focuses on games released between 2021 and 2023.
## Features
- Content-based recommendation: Analyzes game tags, descriptions, and genres to suggest similar games.
- Limited data: Uses data from 2021 to 2023 for recent game releases.
## Installation1. Clone the repository: `git clone https://github.com/Ashishprasa/Steam-Game-Recommendation-System.git`
2. Install dependencies: `pip install -r requirements.txt`
3. After completing the installation, navigate to the cloned repository in the terminal and execute `streamlit run app.py`
4. If you try the Web app without cloning it, I will add the HuggingFace Space under the 'About' section.## Usage
1. Ensure you have the required data in the specified format (tags, descriptions, genres).
2. Run the recommendation script: `streamlit run app.py`
3. Input user preferences.
4. Receive personalized game recommendations.## Data
The project utilizes game data from 2021 to 2023, including titles like "Stray" and "GTA Trilogy".
## Contributions
Contributions are welcome! If you'd like to add features, improve the recommendation algorithm, or fix issues, feel free to submit a pull request.
## License
This project is licensed under the [MIT License](LICENSE).