Chevron Left
Back to ML Pipelines on Google Cloud

Learner Reviews & Feedback for ML Pipelines on Google Cloud by Google Cloud

45 ratings

About the Course

In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. 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. Then we will change focus to discuss how we can automate and reuse ML pipelines across multiple ML frameworks such as tensorflow, pytorch, scikit learn, and xgboost. You will also learn how to use another tool on Google Cloud, Cloud Composer, to orchestrate your continuous training pipelines. And finally, we will go over how to use MLflow for managing the complete machine learning life cycle. Please take note that this is an advanced level course and to get the most out of this course, ideally you have the following prerequisites: You have a good ML background and have been creating/deploying ML pipelines You have completed the courses in the ML with Tensorflow on GCP specialization (or at least a few courses) You have completed the MLOps Fundamentals course. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: <<<...

Top reviews

Filter by:

1 - 11 of 11 Reviews for ML Pipelines on Google Cloud

By Daniel L

Apr 11, 2021

By Gulshat K

Nov 2, 2021

By Javier J

Oct 5, 2021

By Pierre-Yves D

Dec 4, 2021

By Kurapati V S M K

Nov 30, 2021

By Chaitanya K

Sep 3, 2022

By Rodrigo A

Aug 29, 2022

By Médéric H

Mar 7, 2021


Sep 25, 2022

By GianPiero P

Mar 22, 2021

By Parth S

Aug 19, 2022