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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
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.
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.
About Deep learning review.
What do you like best about the product?
As per me in AWS deep learning have some algorithms like RNN, CSS, LSTM and all these technology are good for me.
What do you dislike about the product?
AWS deel learning have some troubleshooting problems like setup error usage error and cleanup errros. So some one need to fix that as soon as possible.
What problems is the product solving and how is that benefiting you?
Sometimes its challenge to solve auto encoders error and they need massive dataset of training. So every one will understand better AWS deep learning.
Prebuilt Docker containers with DL full framework
What do you like best about the product?
We are working on an ML-based project and want to deploy that project in the docker container so we have used aws deep learning docker images so it can help us in many ways :
- less configuration is required to go live in minutes.
- easy to use images for your machine learning application.
- less configuration is required to go live in minutes.
- easy to use images for your machine learning application.
What do you dislike about the product?
All the features mentioned are well developed and as per the documentation nothing to dislike
- as this is managed service so there's a bit of a learning curve required by developers.
- as this is managed service so there's a bit of a learning curve required by developers.
What problems is the product solving and how is that benefiting you?
As we don't have to manage and create the docker images we use this in order to train our model in a faster way and achieve the accuracy also it can improve the speed of application to go live
My Experience about AWS Deep Learning Containers
What do you like best about the product?
AWS Deep Learning Containers made ML operations pretty fast and smooth, Installing and setup of docker has became pretty easy because now we have pre-built frameworkes. we don't have to make container from scratch.
What do you dislike about the product?
It's the UI, for me, I Don't like the user interface which provides by amazon with aws. it is hard to understand. but other than that it is an industry-leading solution for the thing.
What problems is the product solving and how is that benefiting you?
The Hard Part With DL Dockerization is that it is Complicated but, aws helping me and my team to deploy our machine learning dockers easily for larger projects also It has made our lives easy and helped the company a lot.
Best Service Provide by AWS Easily Deploy Container
What do you like best about the product?
The fullness of the service offers really useful images for configuring contexts related to machine knowledge. The structure is authentically well regular and easy to learn. addict interface and stoner peace there was a smooth proficiency with AWS Deep knowledge. Provides us with roustabout pictures pre-installed for deep knowledge architecture.
What do you dislike about the product?
I discovered no downsides whilst the use of the AWS Deep getting to know gadget. The carrier is quickly learned thanks to the easy and intuitive interface. A guide is also available to solve any difficulties. Nothing extra to be advanced, however, yes it could be progressed via supplying diverse OS assistance for Deep gaining knowledge of pics so that improvement can work greater easily
What problems is the product solving and how is that benefiting you?
The hard component With Deep learning Dockerization is that it's complex for Dependency manipulation and AWS managed It properly in form. It helped me plenty in locating the essential pix to load inside the machine learning environment. This allowed me to noticeably lessen the time spent on the usually constructed deep learning framework.
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