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[] Differences in designing for data scientists in general
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Classroom Contents
Machine Learning in Production: A Data Scientist's Perspective from Ubisoft
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- 1 [] Jean-Michel's preferred beverage
- 2 [] Jean-Michel Daignan's background
- 3 [] Takeaways
- 4 [] Rate us and share the podcasts with your friends!
- 5 [] Jean-Michel's projects at Ubisoft
- 6 [] Jean-Michel's success as a Data Scientist
- 7 [] Ubisoft basics
- 8 [] Jean-Michel's success from the downfalls of being a data scientist
- 9 [] Building for data scientists' considerations
- 10 [] Differences in designing for data scientists in general
- 11 [] End twin pipelines and their functions
- 12 [] Major problems doing maintenance
- 13 [] Data quality ownership
- 14 [] Monitoring levels
- 15 [] Locomotive systems
- 16 [] Merlin
- 17 [] DS storage systems
- 18 [] Feature stores batch or streaming?
- 19 [] Bringing Machine Learning to Production at Ubisoft blog post
- 20 [] Features and recommendation systems
- 21 [] Playing games
- 22 [] Play data = play personalities
- 23 [] Deep learning in all the diffusion models or the foundation models
- 24 [] Servicing data scientists' needs
- 25 [] Ubisoft's data volume
- 26 [] Wrap up
