Amazon Deep Learning AMIs

Amazon Deep Learning AMIs

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Score 8.0 out of 100
Amazon Deep Learning AMIs

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What is Amazon Deep Learning AMIs?

AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep…

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  • No setup fee

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  • Free/Freemium Version
  • Premium Consulting / Integration Services

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What is Amazon Lightsail?

Amazon Lightsail is a virtual private server (VPS) designed to present an easy-to-use cloud platform that offers everything needed to build an application or website, plus a cost-effective, monthly plan.

What is Microsoft Azure?

Microsoft Azure is a cloud computing platform and infrastructure for building, deploying, and managing applications and services through a global network of Microsoft-managed datacenters.

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Product Details

What is Amazon Deep Learning AMIs?

AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques.

Amazon Deep Learning AMIs Technical Details

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Reviews and Ratings

 (14)

Reviews

(1-3 of 3)
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Score 10 out of 10
Vetted Review
Verified User
Review Source
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
  • Simpler documentation of different types of AMIs
  • Clearly listing out different types of machines as I got confused and spinned up an AMI in Amazon Linux machine instead of Ubuntu
  • Support for latest version of libraries, to avoid manually updating them after launch
Score 8 out of 10
Vetted Review
Verified User
Review Source
  • You can get several common packages including keras, pytorch and tensorflow setup within an environment ready to code on any AWS instance which saves time
  • Great for virtual applications that helps communicate between various pieces of software
  • Not need to worry about compatibility or any major aspects of setup e.g. GPU configuration
  • Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
  • It can be a bit confusing to switch between frameworks for novice users