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Production Machine Learning Systems, Google 클라우드

4.5
207개의 평가
21개의 리뷰

About this Course

In the second course of this specialization, we will dive into the components and best practices of a high-performing ML system in production environments. Prerequisites: Basic SQL, familiarity with Python and TensorFlow...

최상위 리뷰

대학: AK

Dec 07, 2018

It is very good course, gives good overview over large ML systems on cloud, a lot of examples from real implementations gives good understunding about problematics in projects realisations

대학: AF

May 07, 2019

I did not realize the many aspects to consider implementing a Production ML system. This course presents all of them and provides guidance for evaluating alternative

필터링 기준:

21개의 리뷰

대학: JJ

May 16, 2019

While there is definitely some good and useful content in this course, not all of the material is useful. ~40% of the course felt like a sales pitch, at least to me.

대학: Armando Flores

May 07, 2019

I did not realize the many aspects to consider implementing a Production ML system. This course presents all of them and provides guidance for evaluating alternative

대학: Gregory R. Gray Jr.

Apr 13, 2019

Thumbs Up@

대학: Mirko J. Rodriguez

Apr 02, 2019

Very theoretical.

대학: Cameron S Banowsky

Mar 20, 2019

much meatier of a course.

대학: Facundo Ferrero

Mar 14, 2019

Rich course, although a little tedious, the info is priceless almost all the time. good for consultation

대학: Alexander Kulikov

Feb 10, 2019

excellent

대학: bhadresh savani

Jan 23, 2019

It was bit hard course but lab work was great and learn many production level consideration for ml systems.

대학: Mark Davey

Jan 15, 2019

Very practical which was nice. Thank you for adding the Quicklabs that helped a lot.

대학: Lloyd Palum

Jan 06, 2019

The module on hybrid systems was weak. The time it would take to cover the material would be prohibitive so why do the intro that then apologize for not having the time to explain the material. Leave it out...