Working with AWS DLC significantly accelerates the ML deployment.
What do you like best about the product?
Frequently updating trained images for different frameworks reduced ML time to production.
What do you dislike about the product?
Customizing an AWS DLC still takes time to rebuild. The UI need to be improved.
What problems is the product solving and how is that benefiting you?
The ML Container idea solved many issues in ML deployment:
1) ML model portability
2) ML deployment speed
3) reduced ML production time
1) ML model portability
2) ML deployment speed
3) reduced ML production time
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