A machine learning approach to classify songs by mood.

This is a dataset consisting of all song lyric words found on all of Taylor Swift's studio albums (up to and including TTPD), as well as a selection of other songs written by her.

Based on the idea of Spotify : a concrete example to understand how graph databases work with Neo4j. The challenge is to create a music recommendation algorithm using a very large database of songs (Million Song Challenge Dataset) with an API to interact with (Symfony).

Song lyrics generation using Recurrent Neural Networks (RNNs)

musical snobbery, with a touch of machine learning

Recommending great songs to users based on their listening history!

Song Popularity Predictor

Data Modeling with Postgres

Final Project for STA 141C with Dr. Bo Yu-Chien Ning

Analysis of new songs website data using Postgres SQL Functions to extract insights, business improvement, and understanding the relations between features.

This app simulates a music tracker system on a client-server architecture

ETL Pipeline from AWS S3 to Redshift

Data Engineering Projects: SQL, NoSQL, Data Warehousing, Date Lake & Data Pipeline