How Spotify Does ML At Scale

Case Study

Over 320 million Spotify users in 92 different markets around the globe rely on Spotify’s great recommendations and personalized features. Some users even claim Spotify knows their tastes better than they know them themselves! How does Spotify build these great recs? Unsurprisingly, with data and machine learning! But with the massive inflows of data and complexity of the different pipelines and teams using the data, it’s easy to fall into a trap of tech debt and low productivity. The ML Platform at Spotify was built to address that problem and make all our ML Practitioners productive and happy. How has that turned out? Find out as Aman and Josh describe the history of the ML Platform at Spotify, describe key features like the feature store and the Kubeflow Pipeline engine powering thousands of ML jobs. Come away with an understanding of what Spotify still struggles with and what their plans are for the future.

Session Speakers

Product Manager
Machine Learning Platform Product Lead

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