Music Recommender App using Angular2 similar to Spotify which parses through music metadata to figure out user preferences for a particular song.
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Updated
Nov 15, 2017 - TypeScript
Music Recommender App using Angular2 similar to Spotify which parses through music metadata to figure out user preferences for a particular song.
A Python application that detects user emotions via AI and recommends personalized songs based on emotional state.
musical snobbery, with a touch of machine learning
🎼 Predict the chances of a user listening to a song repetitively after the first observable listening event within a time window was triggered.
Hear the 5 most popular songs of any artist
Checking spotify listening stats and music recommendation
Clustering a twenty thousand song dataset to build a music recomendator.
Design and implementation from scratch of different models for a musical recommendation system
Build a personalized Music Recommendation System using Spotify API and Python. The system uses content-based and hybrid filtering to suggest songs based on user preferences, enhancing the music discovery experience.
Personalized Music Recommender using Word2vec and Gower Similarity.
Drupal site with custom module to scrape a legacy site from webarchive and turn it into a modern Drupal site.
A music recommendation system
A model which can identify similar musical artists based on user listening history from ListenBrainz.
Face recognition, Emotion Detection and Tailored Music Recommendation
Moodify is a Flask-based web application that seamlessly integrates facial emotion recognition (FER) with personalized music recommendations.
performing research survey on neural networks for music classification and recommendation.
An application that recommends music on the basis of previous heard songs of a user using a ML model. Using Collaborative-based filtering to recommend other songs similar to what the user likes. Download Data set from Kaggle (Million song data set)
Music Recommender System Project using Last.FM dataset
This Dataset is a mix of LastFM Artists listened and a map with DBPedia Ontology (metadata). For each Artist there are a link to DBPedia ontology.
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