Music Recommendation Service
Project for CMU 15-780 Graduate Artificial Intelligence
Predict whether a song is 'hot' or not, through analysis of the Million Song Dataset.
Discovery Recommender System
Tools to run text-based experiments for large scale cover detection.
Classying music genre based on audio features and lyrics (using the Million Song Dataset).
Example code for processing the Million Song Dataset and other big music datasets
This repository is inspired from Million Song Dataset Challenge from Kaggle. We aim to predict the year of song release by using timbre features' average and covariance.
This repository implements pre-processing operations of the MELON PLAYLIST DATASET released by Ferraro et al.
Parses the million song dataset/subset from h5 files to two txt files that can easily be used in Pandas, NumPy, or MapReduce
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