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Kursteilnehmer-Bewertung und -Feedback für Production Machine Learning Systems von Google Cloud

4.6
Sterne
749 Bewertungen
81 Bewertungen

Über den Kurs

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-Bewertungen

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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51 - 75 von 81 Bewertungen für Production Machine Learning Systems

von 최일훈

Jun 29, 2019

아주 좋아요

von Logu S

Jul 22, 2020

Good

von Lee M

Jul 02, 2019

good

von 이전규

Jun 23, 2019

good

von Atichat P

Oct 04, 2018

Good

von Prof. R M B

May 13, 2020

ok

von Dustin W

Jun 24, 2020

Not just an issue with this course but it happens with many of the Qwiklab labs. Some of these labs demonstrate complex topics but don't go in to the details. You're given a bunch of command line commands to run which are usually about setting up the environment (local & cloud). Then when it comes to the specific sub-topic (why you're setting these variables) it has very little to say. From that point you're left to research the topic yourself and it can take some time to find it in the documentation. It would be far better if there was call out links to the documentation so I don't have to break my flow of learning taking 15-20 mins to find the information I need in the documentation.

von 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.

von Bhargav D

May 08, 2020

Some modules were amazing and deserved more than 5 stars, other were a little too much. Specifically, everything was great until Kubeflow which I felt was not covered well and the demo not one thing was clear. Very bad demo! Please restructure that demo

von Renato C

Mar 21, 2020

The content and instructors are great. However it shoud not be a two weeks course, as the amount of topics is large.

von Andrei L

May 18, 2020

The course is good. but i would appreciate if it would give more details and more coding exercises

von Steven P G

Aug 11, 2019

Es un curso algo confuso que requiere bastante tiempo para comprender las tematicas

von Mahmmoud M

Mar 07, 2020

very very useful topics to improve and deploying machine learning for productions.

von Nikhileshkumar I

Sep 01, 2019

Great. Ksonnet is not active. Vdo should talk about it.

von Didigam n

Apr 11, 2020

content is nice but too fast

von Hemant D K

Nov 25, 2018

Very Informative.

von PRATHAMESH V B

Jun 11, 2020

Good Experience

von Santosh l

Apr 08, 2020

Excellent

von VIGNESHKUMAR R

Dec 28, 2019

GOOD

von choisungwook

Jul 02, 2019

good

von 길경완

Jun 30, 2019

well

von 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.

von 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...

von 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.

von Junhwan Y

Jun 30, 2019

This course include deep contexts about Machine Learning. But, It's somewhat boring.