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Comentários e feedback de alunos de Production Machine Learning Systems da instituição Google Cloud

4.5
213 classificações
22 avaliações

Sobre o curso

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...

Melhores avaliações

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

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1 — 25 de {totalReviews} Avaliações para o Production Machine Learning Systems

por 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

por bhadresh s

Jan 23, 2019

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

por Mark D

Jan 15, 2019

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

por 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

por 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.

por 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.

por 이전규

Jun 23, 2019

good

por SOYOUNG J

Jun 23, 2019

Great Course

por Kim J W

Jun 18, 2019

very good

por Venkata P I

May 30, 2019

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

por Skander H

May 25, 2019

Really informative and insightful.

por 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.

por Gregory R G J

Apr 13, 2019

Thumbs Up@

por Mirko J R

Apr 02, 2019

Very theoretical.

por Cameron S B

Mar 20, 2019

much meatier of a course.

por Facundo F

Mar 14, 2019

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

por Alexander K

Feb 10, 2019

excellent

por 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...

por Raja R G

Dec 08, 2018

Very informative on production systems....

por Hemant D K

Nov 25, 2018

Very Informative.

por Michael F

Nov 11, 2018

wow gcp michael feldman

por 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.

por 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.

por 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.

por 林佳佑

Oct 20, 2018

very useful for consider data enigerring