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Opiniones y comentarios de aprendices correspondientes a MLOps (Machine Learning Operations) Fundamentals por parte de Google Cloud

4.0
estrellas
326 calificaciones
96 reseña

Acerca del Curso

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 <<<...

Principales reseñas

AM
11 de mar. de 2021

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 de feb. de 2021

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.

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26 - 50 de 96 revisiones para MLOps (Machine Learning Operations) Fundamentals

por Deborishi G

11 de mar. de 2021

Thank you for this opportunity, Google and Training Team!

por khushi

4 de mar. de 2021

its an amazing experience to learn about google cloud

por Reza B

11 de abr. de 2021

Simply a GREAT COURSE, congrats to its designers!!

por Huda M

30 de ene. de 2021

enlighting course, I really enjoyed it

por Shashanka M

10 de feb. de 2021

Somewhat more beginner friendly

por rami k

17 de ene. de 2021

Very nice and smart

por asif m

19 de feb. de 2021

very informative

por Nur C

4 de oct. de 2021

Great course !!

por Akshay W

29 de ene. de 2021

Very Satisfied

por Sathish K T N

22 de ene. de 2021

nice experince

por Harsh S

30 de ene. de 2021

great courses

por Tomy D S

17 de feb. de 2021

nice course

por Ghanshyam J

29 de ene. de 2021

nice course

por vaka j

29 de ene. de 2021

good great

por ABHIJIT B

19 de feb. de 2021

VERY GOOD

por thomas

17 de may. de 2021

super

por Marcio D

30 de mar. de 2021

great

por Dr. S R

26 de jun. de 2021

good

por GOWTHAM G K

6 de feb. de 2021

good

por HARIRAM S

6 de feb. de 2021

good

por Avulla M

26 de ene. de 2021

good

por Vivek S

12 de jun. de 2021

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!!

por Lavi S

22 de feb. de 2021

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.

por Kenneth H

25 de ene. de 2021

Enjoyed the course and it is very interesting. Although there is no formal "prerequisite" for the course, you will get much more if you have various basic concepts in AI/ML, python, Jupyter notebook, CI/CD & Google Cloud Build, K8S & GKE, YAML, Github - especially for the labs, I really enjoy them. You might see some people saying that they hit minor problems - in fact, those minor problems are also part of the learning.

por Ronit S

16 de feb. de 2021

It was amazing course and content. No doubt that you are best content provider for the study material. you are feeling the gap between industry and university. As a learner i also faced some difficulty which you need to review it once in "QUICKLABS" cluster creation.

THANKS :)

Ronit Sagar