musical snobbery, with a touch of machine learning
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Updated
Jul 25, 2016 - Python
musical snobbery, with a touch of machine learning
Google Home assistant for music recommendations, built with Python & Flask. Using Google Home and API.ai
A PyTorch implementation of Matrix Factorization and Factorization Machines
Music recommender system with collaborative and content-based filtering
Recommending Music using a Convolutional Neural Network.
Sequential skip prediction using deep learning and ensembles
Music recommendation system based on personality. Explore your inside symphony! 👨🎤
Graph-based music recommendation engine using NetworkX & Spotify data
This repository contains the work I've did during my masters.
A music recommendation system
Collaborative filtering method using k-nearest neighbors algorithm for music recommendation
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.
KKBox's Music Recommendation Challenge on Kaggle.
create your own spotify recommendation algorithm 🎧
Design, implement and test the effects of a music recommendation system that utilize user emotional data and music preference to recommend songs complimentary to their affect.
Music recommender deployed on heroku
Source code and data for "Fusing Skips and Attention: A Novel Architecture for Session-Based Music Recommendation Using Contextual RNNs". Inspired by the STABR and GRU4REC architectures.
2018 Spotify ACM RecSys Challenge 2'nd Place Solution
This repository implements pre-processing operations of the MELON PLAYLIST DATASET released by Ferraro et al.
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