#MusicTech: Experimenting with Data Science and Recommender Systems

This e-book is an evolving summary of my hacks and experiments on data-science, recommender systems, and more globally music discovery. It covers different ways humans and computers can help us to decide what to listen to, and several various building blocks to do so, from Semantic Web technologies to cloud-based Big Data infrastructures. The use cases aim to be fun and entertaining, and they also cover well-known platforms, such as Spotify, Deezer, YouTube or Twitter.