This project is an Anime Recommendation Engine built using machine learning techniques, specifically utilizing cosine similarity for recommendations. It provides personalized anime recommendations based on user preferences and past interactions.
- Cosine Similarity: Measures the similarity between users' preferences and anime features.
- Firebase Integration: Uses Firebase as the backend database to store user data and interactions.
- Web Interface: Interactive web interface for users to get recommendations.
- Python 3.6 or higher
- Flask
- pandas
- scikit-learn
- numpy
- Firebase Admin SDK
- Navigate to the project directory:
cd Anime-recommendation-Engine-using-ML
- Install the required packages:
pip install -r requirements.txt
- Set up Firebase:
- Follow the instructions on the Firebase Console to create a project and obtain the
serviceAccountKey.json
file. - Place the
serviceAccountKey.json
file in the project directory.
- Follow the instructions on the Firebase Console to create a project and obtain the
- Run the application:
python app.py
- Open your browser and go to
http://127.0.0.1:5000/
to access the web interface.
app.py
: Main application script.anime.csv
: Dataset containing information about various anime.data.csv
: Dataset containing user interaction data.serviceAccountKey.json
: Firebase service account key.templates/
: HTML templates for the web interface.static/
: Static files (CSS, JavaScript) for the web interface.
- Python 3.6 or higher
- A modern code editor like Visual Studio Code
- Web browser (Chrome, Firefox, etc.)
live site: https://anime-recommendation-engine-using-ml-khmb.onrender.com/