October 28–31, 2019
Keshi Dai

Keshi Dai
Machine Learning Engineer, Spotify

Keshi Dai is a machine learning engineer at Spotify, working to build out ML infrastructure that supports hundreds of engineers and the growth of ML in products at Spotify. Previously, Keshi worked on the other side of ML as one of the engineers building out recommendation products at Spotify. He knows firsthand the challenges presented when productionizing ML and the benefit in using standard infrastructure in many parts of the workflow.


1:40pm2:20pm Wednesday, October 30, 2019
Location: Grand Ballroom A/B
Josh Baer (Spotify), Keshi Dai (Spotify)
Average rating: ****.
(4.00, 1 rating)
Josh Baer and Keshi Dai discuss how Spotify has historically used ML and explore how the introduction of TensorFlow and TFX in particular has standardized its ML workflows and improved its ability to bring ML-powered products to its users. Read more.
  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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