Implementing MLOps practices
summary
Describes the phases companies need to build MLOps foundations using a maturity model, explaining how multiple roles collaborate across those phases. Covers purpose-built tools and integrations in Amazon SageMaker that accelerate enterprise ML adoption.
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chapters (10)
- 0:00Introduction
- 4:40Traditional ML challenges
- 7:11What is MLOps
- 11:27SageMaker pipelines
- 15:40SageMaker integration
- 27:05Demo: Pipeline creation
- 33:32Model registry and deployment
- 37:50Maturity model and best practices
- 40:44Security and governance
- 41:45Resources and closing
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