This project is an Anime Recommendation System built with Flask, a Python web framework. It utilizes machine learning techniques such as K-means clustering and TF-IDF vectorization to recommend anime titles based on user input.

• Anime Recommendation: Users can input the title of an anime, and the system will recommend similar anime titles based on machine learning models.
• Fuzzy String Matching: The system uses fuzzy string matching to find the closest matching anime title to the user input, improving accuracy.
• Personalized Recommendations: Recommendations are tailored to the user's genre of anime title they inputed, providing personalized anime suggestions based on type of anime they usually watch.

• Flask: Python web framework used for backend development.
• Pandas: Library for data manipulation and analysis.
• Scikit-learn: Library for machine learning tasks such as clustering and vectorization.
• FuzzyWuzzy: Library for fuzzy string matching.
• HTML/CSS: Frontend for user interface design.

1. Clone the repository:

   git clone https://github.com/your-username/anime-recommendation-system.git

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Flask app:

   python app.py

Open a web browser and navigate to http://localhost:5500.

This project can be deployed with any platforms possible. Ensure to set up environment variables and configure the deployment settings accordingly. I personally already deployed it with GCP and zeet as a third party tool to deploy this project. LINK: https://anime-recommendation-system-kmeans-clustering-21w-5qnji3asoq-as.a.run.app/

Contributions are welcome! If you'd like to contribute to this project, please fork the repository and create a pull request. Feel free to open an issue to report bugs or suggest new features. Thank you!!