Implement a content-based and collaborative filtering recommendation systems for song recommendations.
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Updated
Mar 24, 2020 - Jupyter Notebook
Implement a content-based and collaborative filtering recommendation systems for song recommendations.
Content based Music Recommendation System
Content Based Music Recommendation Service
The goal for this project is to create an LLM based music recommendation system. This project is currently in its very early stages, however the goal of this project is to create an extremely flexible music recommendation system using a chat focused LLM on the frontend to interact with a robust recommendation system on the backend.
Intelligence Where You'll Get Your Next Music. Industrial Training Project 2019. under the guidance of Ardent Computech Pvt. Ltd.
The Music Mood Lifter is a software system empowered by machine learning algorithms that can detect facial expressions from input faces.
This Project is a music recommender based on the spotify's music database
A Music Recommendation System Based on Sound Content
Music recommender using Flask, PostgreSQL and the Spotify API
A simple music recommendation app that uses Flet for UI and an API using the Spotify Web API
Emotion based music recommender system
This repository contains a web application that integrates with a music recommendation system, which leverages a dataset of 3,415 audio files, each lasting thirty seconds, utilising a Locality-Sensitive Hashing (LSH) implementation to determine rhythmic similarity, as part of an assignment for the Fundamental of Big Data Analytics (DS2004) course.
This project summarizes the basic steps required to implement a basic recommendation engines that suggests new bands to users. Data are fetched from the open dataset of ListenBrainz in Bigquery. The recommendation engine is built by hacking the keras embedding layers to perform matrix factorization.
Implementing a music recommender with decision tree.
a Node.js API that interacts with the Spotify API to fetch user data, currently playing track, top tracks, and other Spotify functionalities.
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 using the Decision Tree Classifier
The laboratory from Algorithmic Machine Learning Course at EURECOM
A website that lets you interact with the Spotify recommendations API. Sample new music in over 100 genres based on your current top tracks, their musical attributes, your own personal taste and mood. Add new tracks you might like to your Spotify liked songs playlist.
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