GitHub / huzaifakhan04 / music-recommendation-web-application-based-on-rhythmic-similarity-using-locality-sensitive-hashing

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.

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Topics: ann, approximate-nearest-neighbors, audio-processing, audio-recommendation, audio-segmentation, big-data, cosine-distance, data-science, flask-application, locality-sensitive-hashing, lsh, machine-learning, music, music-information-retrieval, music-recommendation, music-recommendation-system, spotify, web-application

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• Readme
• Dependencies