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Amazon Sagemaker

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.

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Lymphoma Subtype Classification

Latest Version:
0.1
Classifies non-Hodgkin’s Lymphoma subtypes

    Product Overview

    Non-Hodgkin lymphoma (also known as non-Hodgkin’s lymphoma, NHL, or sometimes just lymphoma) is a cancer that starts in white blood cells called lymphocytes, which are part of the body’s immune system. This model illustrates the potential of Deep Learning - in contributing to the automation of cancer diagnosis, by proposing a method to classify the subtypes of Lymphoma. This model is not intended for medical and diagnostic purpose.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Multi-class classifier model that classifies Lymphoma Images as Chronic Lymphocytic Leukaemia, Follicular and Mantle Cell Lymphoma

    • Trained using AlexNet (CNN Architecture)

    • Acknowledgement: Janowczyk A, Madabhushi A. Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases. J Pathol Inform 2016;7:29. (http://www.andrewjanowczyk.com/use-case-7-lymphoma-sub-type-classification/ )

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    Pricing Information

    Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.


    Estimating your costs

    Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.

    Version
    Region

    Software Pricing

    Model Realtime Inference$0.00/hr

    running on ml.m4.xlarge

    Model Batch Transform$0.00/hr

    running on ml.m4.xlarge

    Infrastructure Pricing

    With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
    Learn more about SageMaker pricing

    SageMaker Realtime Inference$0.24/host/hr

    running on ml.m4.xlarge

    SageMaker Batch Transform$0.24/host/hr

    running on ml.m4.xlarge

    Model Realtime Inference

    For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.
    InstanceType
    Realtime Inference/hr
    ml.m4.xlarge
    Vendor Recommended
    $0.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Download the Jupyter notebook in "Additional Resources" section and follow readme.txt provided.

    End User License Agreement

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

    Support Information

    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.

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    Refund Policy

    Since you are not being charged currently for the use of this software there will be no refund of any charges.

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