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Aura is an emotion-aware music recommender that understands your mood from natural language input. It uses a fine-tuned BERT model trained on the GoEmotions dataset to detect your emotion. Based on the emotion, Aura suggests a song to comfort your mood or celebrate it through music.

The purpose of this Personalized Music Recommendation Engine is to use reinforcement learning approach to build a music recommender system and to formulate the problem of interactive recommendation as a contextual multi-armed bandit, learning user preferences recommending new songs and receiving ... Read more

This repository contains the implementation of a Music Recommendation System using the Spotify dataset from Kaggle. The system is built with Machine Learning techniques to suggest songs to users based on their listening history and preferences.

A Music Recommendation System Based on Sound Content

KKBox's Music Recommendation Challenge on Kaggle.

基于Spark MLlib ALS的音乐推荐系统

No description available from source.

No description available from source.

MelodyMind offers personalized music recommendations, from a real-time Last.fm API-powered app to an advanced hybrid system combining content-based and collaborative filtering with LightFM.

A simple Music Recommender system built using Collaborative filtering and Spotify API. Built on top of MERN stack