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.

• 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.

1. 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.

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.

The project utilizes game data from 2021 to 2023, including titles like "Stray" and "GTA Trilogy".

Contributions are welcome! If you'd like to add features, improve the recommendation algorithm, or fix issues, feel free to submit a pull request.

This project is licensed under the MIT License.