saks0106/anime-recommendation-systems

This Repository will recommend Animes until 2023.

Anime Recommendation System

App Link https://saks0106-anime-recommendation-systems-app-alcoiv.streamlit.app/

Project Description:

Dependencies

pip install -r requirements.txt

Ensure you have the following dependencies installed: Python 3. + TensorFlow Keras NumPy Matplotlib Pandas Seaborn Plotly

Overview

Welcome to the Anime Recommendation System! This system is designed to help users discover new anime based on your preferences and interests. By leveraging machine learning algorithms and user interactions, the system aims to provide personalized recommendations to enhance the anime-watching experience and discover some hidden gems.

Features

Anime Database:

A comprehensive database of anime titles, including information like genres, ratings, synopsis, episodes, aired date, duration, ranking, popularity and urls for Anime titles

Recommendation Algorithm

Utilizes item based filtering and content-based filtering to suggest anime. Considers user preferences, their favourite, rankings and community trends.

Search and Filtering:

Users can search for specific anime titles or filter recommendations based on various criteria depending upon which type of recommendations system they choose.

User Interaction:

Users can play with Genres, Keywords The system adapts recommendations based on user interactions.

Responsive UI:

A user-friendly interface accessible through web or mobile devices.

Search and Discover:

Explore anime titles, search for specific ones, or filter recommendations.

Typical Workflow for Data Cleaning, Manipulation and Analysis:

For More information: Check notebooks/Anime EDA.ipynb

Typical Modelling Workflow:

For More information: Check notebooks/Anime Recommendation.ipynb

Training History i.e Plotting Loss

Contributing

Contributions are welcome! If interested in improving the recommendation algorithm, adding new features, or fixing bugs, feel free to submit pull requests.