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ML Pipelines on Google Cloud(으)로 돌아가기

Google 클라우드의 ML Pipelines on Google Cloud 학습자 리뷰 및 피드백

3.6
별점
45개의 평가

강좌 소개

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: https://qwiklabs.com/terms_of_service <<<...

최상위 리뷰

필터링 기준:

ML Pipelines on Google Cloud의 11개 리뷰 중 1~11

교육 기관: Daniel L

2021년 4월 11일

교육 기관: Gulshat K

2021년 11월 2일

교육 기관: Javier J

2021년 10월 5일

교육 기관: Pierre-Yves D

2021년 12월 4일

교육 기관: Kurapati V S M K

2021년 11월 30일

교육 기관: Chaitanya K

2022년 9월 3일

교육 기관: Rodrigo A

2022년 8월 29일

교육 기관: Médéric H

2021년 3월 7일

교육 기관: BHASKAR K

2022년 9월 25일

교육 기관: GianPiero P

2021년 3월 22일

교육 기관: Parth S

2022년 8월 19일