Chevron Left
Back to Production Machine Learning Systems

Learner Reviews & Feedback for Production Machine Learning Systems by Google Cloud

4.5
213 ratings
22 reviews

About the 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...

Top reviews

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

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

Filter by:

1 - 25 of 26 Reviews for Production Machine Learning Systems

By Armando F

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

By bhadresh s

Jan 23, 2019

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

By Mark D

Jan 15, 2019

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

By Artur K

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

By Cristobal S

Oct 29, 2018

While most of the content is sufficiently informative for a course, the implementation itself has too many issues: wrong videos in some modules, errors in quizzes, and so on. Once they organize the material properly, this course can definitely be 5 stars.

By Sinan G

Oct 27, 2018

A lot of great production examples, labs and reviews but perhaps too many issues for a single course - however I understand that it was perhaps to provide an overview of the possibilities, a kind of "toolbox" for production ML.

By 이전규

Jun 23, 2019

good

By SOYOUNG J

Jun 23, 2019

Great Course

By Kim J W

Jun 18, 2019

very good

By Venkata P I

May 30, 2019

very good information. Lot of unknown facts in ML are brought up in the course.

By Skander H

May 25, 2019

Really informative and insightful.

By 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.

By Gregory R G J

Apr 13, 2019

Thumbs Up@

By Mirko J R

Apr 02, 2019

Very theoretical.

By Cameron S B

Mar 20, 2019

much meatier of a course.

By Facundo F

Mar 14, 2019

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

By Alexander K

Feb 10, 2019

excellent

By Lloyd P

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...

By Raja R G

Dec 08, 2018

Very informative on production systems....

By Hemant D K

Nov 25, 2018

Very Informative.

By Michael F

Nov 11, 2018

wow gcp michael feldman

By Carlos V

Nov 11, 2018

This Course has excellent explanations and advice on how to move your models into production and make sure they are reliables and don't lose accuracy over time. The course illustrates how to use the entire ecosystem on GCP that is impressive, quite happy with the explanation and the expert's advice.

By Harold L M M

Nov 08, 2018

Overall rating is 3 out of 5, as I expected more of the initial line in the first course. The optional Kubeflow lab has issues, as the ksonnet apply command line halts. Also, the last lab was expected to allow the student to code more, as this is the only way to make a person to gain more insights on the architecture.

By Jun W

Nov 04, 2018

This course reveals some practical techniques in Production Machine Learning Systems. I like the real world examples introduced in this course.

By 林佳佑

Oct 20, 2018

very useful for consider data enigerring