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Отзывы учащихся о курсе MLOps (Machine Learning Operations) Fundamentals от партнера Google Cloud

4.0
звезд
Оценки: 303
Рецензии: 93

О курсе

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models. This course is primarily intended for the following participants: Data Scientists looking to quickly go from machine learning prototype to production to deliver business impact. Software Engineers looking to develop Machine Learning Engineering skills. ML Engineers who want to adopt Google Cloud for their ML production projects. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<...

Лучшие рецензии

AM
11 мар. 2021 г.

The whole process of building the Kubeflow pipelines for MLOPs including the configuration part (what does into the Dockerfile, cloud build) has been explained fully.

DM
1 февр. 2021 г.

Thank You , Coursera & Google, It was great session & learn some practical Aspects & fundamentals of ML. I hope it will help me in the future. Thank You.

Фильтр по:

1–25 из 93 отзывов о курсе MLOps (Machine Learning Operations) Fundamentals

автор: Ruhua J

8 дек. 2020 г.

The content is decent. But the labs are pretty broken, not well designed & maintained

автор: Satrio W P

17 дек. 2020 г.

Qwiklabs does not work!!

автор: Arthur J

8 дек. 2020 г.

There's a few things underwhelming about this course. First, GCP has made MLops very complicated, technical and cumbersome. Since you would need to work with this tech on a regular basis, you really don't want this. Second, the tutorials are mostly challenging due to linux. The tutorials are also buggy and setting up the cloud resources takes a lot of time. Overall, not that happy with this course or the subject mater.

автор: Joana M

4 янв. 2021 г.

The qwiklabs have many issues, and due to the limited amount of tries I was not able to complete the course.

автор: Kshitiz R

30 дек. 2020 г.

By far the worst experience. Videos and explanations are really good but all those goodness are killed by the Qwiklabs experience. Labs are frustrating because they don't simply work, not because you did something wrong. I would like to urge the team behind this course to put some effort and time fixing those labs and answer to the questions raised by the learners in discussion forums. By copy pasting the readymade answer to email qwiklabs support team won't help at all.

автор: Hugo P

31 дек. 2020 г.

The Labs could be improved (bugs and clarity)

автор: Jon M

1 янв. 2021 г.

The content related to MLOps on GCP is quite good. If the labs were improved slightly to remove some of the bugs that are commonly posted in the message boards, this would be a 5 star.

автор: Peng L

12 дек. 2020 г.

Course content was good. However, many of the Qwiklabs had bugs, resulting in not being able to complete the course with a grade of 100%.

автор: Artur Y

11 янв. 2021 г.

Some labs are impossible to complete due to incompatibility with github. Github requires verification email.

автор: Tarun K

19 февр. 2021 г.

This was a good course along with google qwiklab which guide you through out the lab which makes a enrolled person a successful learner .

автор: Surachart O

12 нояб. 2020 г.

Great course to start for learning about MLOps. However, I hope there will have more videos to explain details on LABs.

автор: Dmitriy K

10 дек. 2020 г.

I liked it. Made me realize how much of a pain MLOps really is.

автор: Priyanka A

23 февр. 2021 г.

VERY HELPFUL AND KNOWLEDGE BASED COURSE. THANKS TO ALL THE INTRUCTORS.

автор: Anshumaan K P

16 янв. 2021 г.

Some Labs isn't working properly

автор: nerisha s

30 нояб. 2020 г.

Accent is difficult to understand. Speaks to quickly. Cannot read subtitles and course content at the same time.

автор: zeroone_ai

28 апр. 2021 г.

quiklabs always have a trouble when I try this cource..

автор: Dinesh K R

17 апр. 2021 г.

This is one of the best course to start on ML OPS with GCP. The Concepts were explained neatly throughout the course, and i am sure this would really help me to solve the most complex use cases in deploying ML Models. Thanks Google for this wonderful course and many appreciations to Qwiklabs for hands-on. Highly recommended for ML Engineers/ Data Scientist.

автор: Aparna M

12 мар. 2021 г.

The whole process of building the Kubeflow pipelines for MLOPs including the configuration part (what does into the Dockerfile, cloud build) has been explained fully.

автор: Darshankumar N M

2 февр. 2021 г.

Thank You , Coursera & Google, It was great session & learn some practical Aspects & fundamentals of ML. I hope it will help me in the future. Thank You.

автор: Shreyas R C

7 июля 2021 г.

Well designed course with Qwiklabs hands-on experience, awesome learning. Thanks to Google Cloud Team and Coursera

автор: Dipanjan B

30 янв. 2021 г.

excellent experience. thank you very much coursera and google to give the oppurtunity to get certificate free.

автор: Hammam A

11 мар. 2021 г.

Very informative. Provides the basic needs to understand creating ml pipelines.

автор: Pasquinell U

15 июня 2021 г.

course is good, but need more diagrams. Visual maps help wrapping concepts.

автор: Suprava S

29 янв. 2021 г.

Excellent Curriculum. I enjoyed the whole lab assignments and the quiz.

автор: Uday K S

29 янв. 2021 г.

Very good learning platform for Machine Learning Fundamentals