Opiniones y comentarios de aprendices correspondientes a Build, Train, and Deploy ML Pipelines using BERT por parte de deeplearning.ai
Acerca del Curso
Principales reseñas
It is one of course with the exact content required for an working professional who is already working with AWS and want to leverage the benefits of sagemaker for their ML deployment tasks
Simple to learn but there are lot of takeaways which helps any data scientist or a machine learning engineer!
1 - 10 de 10 revisiones para Build, Train, and Deploy ML Pipelines using BERT
por Israel T
•Great for introduction to the AWS Sagemaker tools. But if you really want to dive deeper on the tools, you need to add and explore other resources, since most of the codes are already provided in the exercise.
por Pablo A B
•Gives good general overview of Pipelines. However, assignments are way too easy, which makes them not to add too much to the learning.
por Magnus M
•The videos are excellent. The labs are way too easy, just copying some variable names.
por Sneha L
•It is one of course with the exact content required for an working professional who is already working with AWS and want to leverage the benefits of sagemaker for their ML deployment tasks
por yugesh v
•Simple to learn but there are lot of takeaways which helps any data scientist or a machine learning engineer!
por Ozma M
•EXcellent MLOps content, presentation, demo
por Tenzin T
•Highly recommended
por Alexander M
•Week 3 lab gave twice error 'Failed' and 3rd time it went without an issue. This was quite frustrating. Overall, good class. Thx.
por Mosleh M
•ok
por Mark P
•Coding exercises are a bit too structured, there isn't as much learning as I would have liked. That said, having the notebooks for reference at work is quite useful. Good introduction.
Coursera Footer
