Description

We covered:

• What is MLOps
• The difference between MLOps and ML Engineering
• Getting into MLOps
• Kubeflow and its components, ML Platforms
• Learning Kubeflow
• DataOps 

And other things

Links:

• Microsoft MLOps maturity model: https://docs.microsoft.com/en-us/azure/architecture/example-scenario/mlops/mlops-maturity-model
• Google MLOps maturity levels: https://cloud.google.com/solutions/machine-learning/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning
• MLOps roadmap 2020-2025: https://github.com/cdfoundation/sig-mlops/blob/master/roadmap/2020/MLOpsRoadmap2020.md
• Kubeflow website: https://www.kubeflow.org/
• TFX Paper: https://research.google/pubs/pub46484/

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