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很好
The AWS Deep Learning Containers for PyTorch include containers for training and inference for CPU and GPU, optimized for performance and scale on AWS. These Docker images have been tested with SageMaker, EC2, ECS, and EKS and provide stable versions of NVIDIA CUDA, cuDNN, Intel MKL
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The usage is quite logical and output is reasonable
What do you like best about the product?
In deep learning most time constraints are there so saving time with investing much time is good approach
What do you dislike about the product?
As long as hanging in loop need to relook
What problems is the product solving and how is that benefiting you?
Mostly NLP
The usage is quite logical and output is reasonable
What do you like best about the product?
In deep learning most time constraints are there so saving time with investing much time is good approach
What do you dislike about the product?
As long as hanging in loop need to relook
What problems is the product solving and how is that benefiting you?
Mostly NLP
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
Best for easily deploying coustom ml environments
What do you like best about the product?
It is very easy to just skip through the difficult process of building and deploying the environment scratch and we can let easily deploy ML environments. It is better from others as we can just use it to have pre installed docker images.
What do you dislike about the product?
Nothing it is which is not likeable about the AWS deep learning container.
What problems is the product solving and how is that benefiting you?
It lets us skip the complicated part of developing and deploying the environment from scratch each time the requirements come up, we can use the pre installed docker images, create templates and containers , in just few click we are ready to launch a new ML environment when need comes up.
Best for easily deploying coustom ml environments
What do you like best about the product?
It is very easy to just skip through the difficult process of building and deploying the environment scratch and we can let easily deploy ML environments. It is better from others as we can just use it to have pre installed docker images.
What do you dislike about the product?
Nothing it is which is not likeable about the AWS deep learning container.
What problems is the product solving and how is that benefiting you?
It lets us skip the complicated part of developing and deploying the environment from scratch each time the requirements come up, we can use the pre installed docker images, create templates and containers , in just few click we are ready to launch a new ML environment when need comes up.
AWS Deep Learning Containers Review
What do you like best about the product?
This AWS Deep learning containers structure is very easy to learn. Smooth proficiency with deep knowledge. Not much of the configuration is required to go live on the go. Images can be easily used. The machine learning operation made easy with AWS deep learning containers.
What do you dislike about the product?
There is the only problem that i think needs to be corrected is the troubleshooting problem of error. Otherwise, all is good and smooth with these AWS deep learning containers.
What problems is the product solving and how is that benefiting you?
The manual Image creation was a problem that is being solved because of this AWS deep learning we can do it in more smooth and fast manner.
AWS Deep Learning Containers Review
What do you like best about the product?
This AWS Deep learning containers structure is very easy to learn. Smooth proficiency with deep knowledge. Not much of the configuration is required to go live on the go. Images can be easily used. The machine learning operation made easy with AWS deep learning containers.
What do you dislike about the product?
There is the only problem that i think needs to be corrected is the troubleshooting problem of error. Otherwise, all is good and smooth with these AWS deep learning containers.
What problems is the product solving and how is that benefiting you?
The manual Image creation was a problem that is being solved because of this AWS deep learning we can do it in more smooth and fast manner.
Amazing service for Deep Machine Learning.
What do you like best about the product?
This service by AWS made the operations pretty smooth in our machine learning applications. The ease of use and the pre built containers are a big help in our ongoing projects.
What do you dislike about the product?
The service is pretty sleep but the interface could be slightly user-friendlier.
What problems is the product solving and how is that benefiting you?
The team is happy with the ability of the AWS deep learning container service to perform the tasks in the project, and the prebuilt library they provide. speeding up the process.
Amazing service for Deep Machine Learning.
What do you like best about the product?
This service by AWS made the operations pretty smooth in our machine learning applications. The ease of use and the pre built containers are a big help in our ongoing projects.
What do you dislike about the product?
The service is pretty sleep but the interface could be slightly user-friendlier.
What problems is the product solving and how is that benefiting you?
The team is happy with the ability of the AWS deep learning container service to perform the tasks in the project, and the prebuilt library they provide. speeding up the process.
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