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

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

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

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

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.

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.

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

Really informative and insightful.

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.

Thumbs Up@

Very theoretical.

much meatier of a course.

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

excellent

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...

Very informative on production systems....

Very Informative.

wow gcp michael feldman

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.

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.

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

very useful for consider data enigerring

Good