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This product has charges associated with it for seller support. The Deep Learning AMI Amazon Linux is an optimized solution designed for developers and data scientists to accelerate machine learning workflows. It comes pre-installed with popular deep learning frameworks such as TensorFlow, PyTorch, and MXNet, along with a wide range of libraries for data manipulation and visualization. Benefit from built-in GPU support to enhance the performance of your models and reduce training time significantly. This AMI also supports Jupyter notebooks, making it easy to develop, test, and deploy your deep learning applications in the EC2 cloud. Ideal for industries like healthcare, finance, and autonomous systems, the Deep Learning AMI simplifies the complex process of setting up a deep learning environment, allowing you to focus on innovation rather than infrastructure.
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Overview
This is a repackaged open source software wherein additional charges apply for extended support with a 24 hour response time.
The Deep Learning AMI on Amazon Linux provides a comprehensive, flexible, and scalable environment specifically designed for deep learning tasks. Engineered for machine learning practitioners and researchers, this AMI includes a rich set of pre-installed frameworks, libraries, and tools tailored for the most demanding deep learning applications.
Key Features:
- Pre-installed Frameworks: Comes with popular deep learning frameworks such as TensorFlow, PyTorch, and Apache MXNet, allowing you to start your projects without the hassle of setup.
- Optimized Performance: The AMI is optimized for use with NVIDIA GPUs, enabling efficient training and inference of deep learning models, which significantly accelerates computational tasks.
- Automatic Updates: Regular updates ensure that you have access to the latest features and security improvements for the underlying software stack.
- Integrated Tools: Includes tools for data preprocessing, model training, and deployment, simplifying the workflow of building deep learning models.
- Jupyter Notebooks: Supports Jupyter notebooks, providing an interactive development environment that is user-friendly, making it easier to document experiments and visualize results.
Benefits:
- Enhanced Productivity: Focus on developing and training models rather than spending time on environment setup and configuration.
- Scalability: Easily scale computational resources as needed to match the requirements of your workloads.
- Cost-Efficiency: Utilize Amazon EC2 pricing models to optimize costs by only paying for what you use, while leveraging powerful cloud-based computing.
Use Cases:
- Research and Development: Ideal for researchers building and testing deep learning algorithms.
- Proof of Concept: Quick deployment for developing proofs of concept for machine learning applications.
- Production Workflows: Suitable for organizations integrating machine learning into their production environments and workflows.
With the Deep Learning AMI on Amazon Linux, accelerate your deep learning projects in a ready-to-use, cloud-optimized environment designed for researchers and developers alike.
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Highlights
- The Deep Learning AMI based on Amazon Linux provides a robust environment tailored for deep learning professionals. Pre-configured with popular frameworks such as TensorFlow, PyTorch, and MXNet, it allows developers to get started quickly. Users can take advantage of optimized libraries and tools, ensuring high performance and efficiency while training models, enabling seamless transitioning from experimentation to deployment.
- With built-in support for GPU instances, this AMI ensures accelerated computational capabilities, significantly increasing training speeds for complex neural networks. Featuring automatic updates and security patches, it supports a wide range of hardware options, maximizing cost-efficiency. Furthermore, the integration with Amazon SageMaker allows for easy scaling and management of machine learning workflows in production environments.
- This Deep Learning AMI is ideal for data scientists, researchers, and engineers looking to accelerate their machine learning projects. Use cases range from academic research to enterprise-scale AI applications. The flexibility to customize and adapt the environment to specific project needs enhances collaborative efforts across teams, making it a valuable resource for any organization focused on advancing their AI initiatives.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
AmazonLinux 1
Typical total price
This estimate is based on use of the seller's recommended configuration (inf1.6xlarge) in the US East (N. Virginia) Region. View pricing details
$2.30/hour
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covering your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
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Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
t1.micro | $0.07 | $0.02 | $0.09 |
t2.nano | $0.07 | $0.006 | $0.076 |
t2.micro AWS Free Tier | $0.21 | $0.012 | $0.222 |
t2.small | $0.07 | $0.023 | $0.093 |
t2.medium | $0.14 | $0.046 | $0.186 |
t2.large | $0.14 | $0.093 | $0.233 |
t2.xlarge | $0.28 | $0.186 | $0.466 |
t2.2xlarge | $0.56 | $0.371 | $0.931 |
t3.nano | $0.07 | $0.005 | $0.075 |
t3.micro AWS Free Tier | $0.07 | $0.01 | $0.08 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp2) volumes | $0.10/per GB/month of provisioned storage |
Vendor refund policy
The instance can be terminated at anytime to stop incurring charges
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
System Updates
Additional details
Usage instructions
SSH to the instance and login as 'ec2-user' using the key specified at launch.
OS commands via SSH: SSH as user 'ec2-user' to the running instance and use sudo to run commands requiring root access.
More on using Deep Learning AMI with Conda: https://docs.thinkwithwp.com/dlami/latest/devguide/tutorial-conda.html
Resources
Vendor resources
Support
Vendor support
Email support for this AMI is available through the following: https://supportedimages.com/support/ OR support@supportedimages.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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