Personalizing Spotify Home with Machine Learning
Machine learning is at the heart of everything we do at Spotify. Especially on Spotify Home, where it enables us to personalize the user experience and provide billions of fans the opportunity to enjoy and be inspired by the artists on our platform. This is what makes Spotify unique.
Across our engineering community, we are working to unite autonomous teams and empower them to be more efficient by establishing best practices for tools and methods. Our recent adoption of a standardized machine learning infrastructure provides our engineers with the environment and tools that enable them to quickly create and iterate on models. We call it our ‘Paved Road’ approach, which includes utilizing services from TensorFlow, Kubeflow, and the Google Cloud Platform.
Before coming to Spotify, I worked on personalization algorithms and the home screen at Netflix. My previous experience is quite similar to the work I’m doing now at Spotify as the Vice President of Engineering and Head of Machine Learning. However, personalizing Spotify’s Home screen presented a new set of challenges, which I’ll share later.