Completed
[] Low-latency ingestion that powers real-time feature pipelines
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Classroom Contents
Tecton 0.6: Notebook-driven Development for Feature Engineering - MLOps Meetup
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- 1 [] Musical intro for Jason Dunne
- 2 [] Notebook-driven Development
- 3 [] Tecton 0.6: Agenda
- 4 [] Real-Time ML
- 5 [] Uber Eats: Real-Time ML At Scale
- 6 [] Building Real-Time systems is hard. Maintaining them is harder
- 7 [] Tecton Feature Platform Overview
- 8 [] Tecton allows teams to quickly and reliably transform and serve data for ML applications, at scale.
- 9 [] Tecton Feature Platform: Design, Build, Centralize, Serve, and Manage Features for Production ML
- 10 [] Tecton is the Feature Platform of choice for leading ML teams across industries and use cases
- 11 [] 0.6 Core Capabilities
- 12 [] Public Preview: Notebook-driven Development
- 13 [] Notebook-driven Development reduces the number of steps for developers creating new features
- 14 [] Notebook-driven Development Demo
- 15 [] Tecton's Feature Platform
- 16 [] Feature depends on another feature
- 17 [] Production flow
- 18 [] Difference from TDD
- 19 [] Low-latency ingestion that powers real-time feature pipelines
- 20 [] Sufferance from sweet test labeling
- 21 [] Being self-hosted
- 22 [] Notebook cluster
- 23 [] Wrap up
