ML Pipelines on Google Cloud by Coursera

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Course Features

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Duration

11 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Teaching Type

Self Paced

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Video Content

11 hours

Course Description

This course will teach you from ML Engineers and Trainers, who are involved in the development of ML pipelines at Google Cloud. TensorFlow Extended (or TFX) will be the first module. This is Google's machine learning platform that uses TensorFlow to manage ML pipelines and metadata. Learn about pipeline components and how to orchestrate your pipeline with TFX. Learn how to automate your pipeline with continuous integration and continuous deployment. Also, how to manage metadata ML.

Next, we'll shift our focus to how we can reuse ML pipelines across multiple ML frameworks like tensorflow and pytorch. Cloud Composer is another tool that Google Cloud offers to help you manage your continuous training pipelines. Finally, we'll cover how to use MLflow to manage the entire machine learning lifecycle. This course is for advanced learners only. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

Course Overview

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Skills You Will Gain

What You Will Learn

You will learn about pipeline components and pipeline orchestration with TFX

You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Course Instructors

Google Cloud Training

Instructor

The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an ef...

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