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Вернуться к MLOps (Machine Learning Operations) Fundamentals

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

Оценки: 355

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: <<<...

Лучшие рецензии


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.


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:

26–50 из 103 отзывов о курсе MLOps (Machine Learning Operations) Fundamentals

автор: Martin S

12 февр. 2022 г.

Videos are good, a lab was initially broken but fixed in a few days.

автор: Uday K S

29 янв. 2021 г.

Very good learning platform for Machine Learning Fundamentals

автор: Deborishi G

11 мар. 2021 г.

Thank you for this opportunity, Google and Training Team!

автор: khushi

4 мар. 2021 г.

its an amazing experience to learn about google cloud

автор: Reza B

11 апр. 2021 г.

Simply a GREAT COURSE, congrats to its designers!!

автор: Huda M

30 янв. 2021 г.

enlighting course, I really enjoyed it

автор: Shashanka M

10 февр. 2021 г.

Somewhat more beginner friendly

автор: rami k

17 янв. 2021 г.

Very nice and smart

автор: asif m

19 февр. 2021 г.

very informative

автор: Nur C

4 окт. 2021 г.

Great course !!

автор: Akshay W

29 янв. 2021 г.

Very Satisfied

автор: Sathish K T N

22 янв. 2021 г.

nice experince

автор: Harsh S

30 янв. 2021 г.

great courses

автор: Tomy D S

17 февр. 2021 г.

nice course

автор: Ghanshyam J

29 янв. 2021 г.

nice course

автор: vaka j

29 янв. 2021 г.

good great

автор: ABHIJIT B

19 февр. 2021 г.


автор: thomas

17 мая 2021 г.


автор: Marcio D

30 мар. 2021 г.


автор: Dr. S R

26 июня 2021 г.


автор: GOWTHAM G K

6 февр. 2021 г.


автор: HARIRAM S

6 февр. 2021 г.


автор: Avulla M

26 янв. 2021 г.


автор: Vivek S

12 июня 2021 г.

MLOps fundamentals is a good introduction, great teachers! The only place that I feel needs improvement is the lab - it would be great if there is more time to do the exercises, the lab gets timed out at 2 hrs. Sometimes the lab instruction are not very clear. Also I would be happier If the instructors went through other build tools like Bazel, etc.... This course helped organize ML workflows and make it easier to experiment, deploy and iterate over model dev.... Overall a very good course!!

автор: Lavi S

22 февр. 2021 г.

github repo used throughout the code will probably serve as a good template for my future projects. The quizzes are on the easy end. The labs can be achieved by a series of copy+paste. Some give the full points for just opening the notebooks without even running them (same set of steps in two of the labs that only differ in notebook content). Feels like I have a lot to go before I'll be able to use these tools for my own tasks. Nevertheless - got to start somewhere.