Predicting a hit Song

Using Machine Learning Models to predict a song's popularity.

This is a group project from the Data Science and Advanced Analytics course from the Big Data & Analytics Masters @ EAE class of 2021.

This was our first rough idea

After playing with some tools and online services

Our final work followed this process / artifacts

Linked Repos to the three components

• Preparing additional / artists' data to feed into the model https://github.com/joseph-higaki/music-hit-decorate-datasets
• Analyzing and understanding the data at scale https://github.com/joseph-higaki/music-hit-analyze-data
• Training the models https://github.com/joseph-higaki/music-hit-train-predict

Documentation

1. Business Understanding Presentation
2. Final Presentation
3. Documentation

Future work: How this solution is deployed

Future work: How this solution is monitored/re-trained

Team

(music-hit-decorate-datasets/music-hit-analyze-data/music-hit-train-predict)

• Henrique Avila
• Joseph Higaki (GitHub)
• Raquel Ganuza
• Romain Baleynaud (GitHub)
• Ziyad Ashukri

Professor

• Marta Tolós

Professor Assistants

• Pere Miquel Brull Borràs
• Alberto Villa