Expanded

MLOps (Machine Learning Operations) Fundamentals

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
Course info
Level
Intermediate
Updated
May 10, 2021
Duration
5h 24m
Table of contents
Why and When do we need MLOps
Understanding the main Kubernetes components (Optional)
Introduction to AI Platform Pipelines
Training, Tuning and Serving on AI Platform
Kubeflow Pipelines on AI Platform
CI/CD for Kubeflow Pipelines on AI Platform
Course Summary
Description
Course info
Level
Intermediate
Updated
May 10, 2021
Duration
5h 24m
Description

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

About the author
About the author

Build, innovate, and scale with Google Cloud Platform.

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