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Deep Learning AMI (Ubuntu)

Comes with latest versions of pip packages of popular deep learning frameworks pre-installed in separate virtual environments. Includes Apache MXNet, Caffe2, TensorFlow, PyTorch, Keras, CNTK and Theano as well as packages that enable easy integration with other AWS services. It also includes Anaconda Data Science packages. The AMI is designed to provide a stable, secure, and high performance execution environment for running deep learning applications on Amazon EC2. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.Release tags/Branches used: Apache MXNet 1.0 with Gluon, TensorFlow 1.4, Caffe2 0.8.1, PyTorch 0.3, CNTK 2.2, Theano 0.9, Keras 1.2.2 and Keras 2.0.9, The AMI is also configured with NVidia CUDA 8, CUDA 9, cuDNN 6, cuDNN7, and NVidia Driver 384.81. The deep learning frameworks are pre-configured in separate Conda-based python environments. You can start running your deep learning code in these fully baked virtual environments in minutes. Check out the AMI Developer Guide for how-to guides, detailed release notes and additional resources for the Conda-based deep learning AMI: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html


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    Latest Version

    2.0


    Operating System

    Linux/Unix, Ubuntu 16.04


    Delivery Method

    64-bit Amazon Machine Image (AMI) (Read more)



    AWS Services Required

    Amazon EC2, Amazon EBS


    Highlights

    • Used Ubuntu 16.04 (ami-cd0f5cb6) as the base AMI.
    • Contains the latest versions of most popular Deep Learning Frameworks - Apache MXNet, Caffe2, Tensorflow, PyTorch, Keras, Theano and CNTK.
    • All the deep learning frameworks are installed, and pre-configured in separate Conda-based virtual environments. You can start running your deep learning code in these fully baked virtual environments in minutes.

    Product Description

    Comes with latest versions of pip packages of popular deep learning frameworks pre-installed in separate virtual environments. Includes Apache MXNet, Caffe2, TensorFlow, PyTorch, Keras, CNTK and Theano as well as packages that enable easy integration with other AWS services. It also includes Anaconda Data Science packages. The AMI is designed to provide a stable, secure, and high performance execution environment for running deep learning applications on Amazon EC2. The Deep Learning AMI is provided at no additional charge to Amazon EC2 users.

    Release tags/Branches used:
    Apache MXNet 1.0 with Gluon,
    TensorFlow 1.4,
    Caffe2 0.8.1,
    PyTorch 0.3,
    CNTK 2.2,
    Theano 0.9,
    Keras 1.2.2 and Keras 2.0.9,

    The AMI is also configured with NVidia CUDA 8, CUDA 9, cuDNN 6, cuDNN7, and NVidia Driver 384.81.

    The deep learning frameworks are pre-configured in separate Conda-based python environments. You can start running your deep learning code in these fully baked virtual environments in minutes. Check out the AMI Developer Guide for how-to guides, detailed release notes and additional resources for the Conda-based deep learning AMI: http://docs.aws.amazon.com/dlami/latest/devguide/what-is-dlami.html

    Product Details

    • Version: 2.0
    • Available on AWS Marketplace Since: 11/15/2017

    Resources

    Usage Instructions

    Getting-started guide for Deep Learning AMI: http://docs.aws.amazon.com/dlami/latest/devguide/gs.html

    Read more

    Support Details

    Deep Learning AMI (Ubuntu)

    Support is available through forums, technical FAQs and the Service Help Dashboard. Post your questions to the AWS Deep Learning AMI Discussion Forum

    https://forums.aws.amazon.com/forum.jspa?forumID=263

    AWS Infrastructure

    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. Learn more

    Refund Policy

    The Deep Learning AMI is provided free of charge

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End User License Agreement (EULA).

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    Pricing Details

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    Recent Product Reviews

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