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Welcome to the MM4_2401FTDS-Anime-Recommender-App! This Streamlit app uses collaborative and content-based filtering to predict anime ratings based on user preferences. It offers an interactive interface for personalized anime recommendations.

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Project Overview

DataMinds team has been hired as data science consultants for a news outlet to create classification models using Python and deploy it as a web application with Streamlit. The aim is to improve content categorization for Frontier Times by developing machine learning models to classify articles into categories based on content. This repository contains the code for the final deployment of the application. The primary stakeholders for the news classification project for the news outlet could include the editorial team, IT/tech support, management, readers, etc. These groups are interested in improved content categorization, operational efficiency, and enhanced user experience.

The application is available at: https://frontier-times.streamlit.app/

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Welcome to the MM4_2401FTDS-Anime-Recommender-App! This Streamlit app uses collaborative and content-based filtering to predict anime ratings based on user preferences. It offers an interactive interface for personalized anime recommendations.

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  • Python 93.1%
  • CSS 6.9%