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Anime Recommendation System

An Anime Recommender web app that clusters anime based on collabortive filtering and displays suggestions based on users favorite anime via a web interface using Jikan API.

Features

  • Matrix Factorization using PyTorch for user anime-anime rating predictions
  • KMeans clustering to group similar anime based on learned embeddings
  • Live anime info using Jikan API for search & detailed animes
  • Personliazed Recomemndations from users favorite anime
  • Dynamic Image Fetching for anime visuals

How it works

  1. Model Trainin (PyTorch)
    • Loads user rating data from Kaggle (anime.csv, rating.csv)
    • Applies matrix factorization to learn latent features for users & items
    • Clusters anime embeddings into similar groups using KMeans
    • Store the results into csv
  2. Frontend Interface (HTML + JS)
    • Search anime with Jikan API
    • Displays recommended anime from the same cluster
    • Fetches real-time anime details & images

Link to Notebook

Link to Anime Recommendation Notebook

License

MIT License. Feel free to use and expand!

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