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user-preferences

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🎵 A Python-based content recommendation system utilizing ML algorithms and matrix factorization techniques to analyze 600k-song dataset. Combines SVD, NMF, Factorization Machines, and Direct Similarity for personalized music suggestions. Handles cold start, optimizes with weighted similarity, and includes tools for visualization & evaluation.

  • Updated May 10, 2025
  • Jupyter Notebook

A modern, responsive web application that delivers personalized content recommendations based on user preferences and behavior. This interactive recommendation system allows users to discover content tailored to their interests through category selection, tag filtering, and customizable content parameters.

  • Updated May 2, 2025
  • HTML

This repository contains datasets from our paper, Sentiment-Driven Community Detection in a Network of Perfume Preferences, analyzing perfume preferences based on positive user reviews from Atrafshan, including User Reviews and Perfume Attributes, Emoji Mapping Dictionary, and Sentiment Classification Results.

  • Updated Nov 26, 2024

🎶 Spotify Data Retrieval Script is a Python script that uses Spotipy to interact with the Spotify Web API and retrieve a user's saved tracks, playlists, and recently played tracks. Outputs to console. Great starting point for working with the Spotify API.

  • Updated May 6, 2024
  • Python

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