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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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Mphasis DeepInsights Card Fraud Analyzer

Latest Version:
2.7
Deep Learning powered classification solution generates insights from highly skewed data with relevant class (e.g. fraud cases) < 1% of data

    Product Overview

    DeepInsights Card Fraud Analyzer is a Deep-Learning powered classification solution that provides valuable insights from any data that is highly skewed with relevant class (e.g. fraudulent transactions) being represented by less than 1% of data. The solution works with numerical data and provides best results when input data includes customer’s demographics and transaction history along with current transaction.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Model is first trained and validated on the user provided training data. Trained model can then be deployed in production.

    • The solution works with numerical data and provides best results when input data includes customer’s demographics and transaction history along with current transaction. The analysis can be used for solving multiple problems that require working with highly skewed data and can be extended for multi-class classification problems

    • Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need Customized Deep learning and Machine Learning Solutions? Get in Touch!

    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.

    Contact us to request contract pricing for this product.


    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$10.00/hr

    running on ml.m5.large

    Model Batch Transform$20.00/hr

    running on ml.m5.large

    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$0.115/host/hr

    running on ml.m5.large

    SageMaker Batch Transform$0.115/host/hr

    running on ml.m5.large

    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.m4.4xlarge
    $10.00
    ml.m5.4xlarge
    $10.00
    ml.m4.16xlarge
    $10.00
    ml.m5.2xlarge
    $10.00
    ml.p3.16xlarge
    $10.00
    ml.m4.2xlarge
    $10.00
    ml.c5.2xlarge
    $10.00
    ml.p3.2xlarge
    $10.00
    ml.c4.2xlarge
    $10.00
    ml.m4.10xlarge
    $10.00
    ml.c4.xlarge
    $10.00
    ml.m5.24xlarge
    $10.00
    ml.c5.xlarge
    $10.00
    ml.p2.xlarge
    $10.00
    ml.m5.12xlarge
    $10.00
    ml.p2.16xlarge
    $10.00
    ml.c4.4xlarge
    $10.00
    ml.m5.xlarge
    $10.00
    ml.c5.9xlarge
    $10.00
    ml.m4.xlarge
    $10.00
    ml.c5.4xlarge
    $10.00
    ml.p3.8xlarge
    $10.00
    ml.m5.large
    Vendor Recommended
    $10.00
    ml.c4.8xlarge
    $10.00
    ml.p2.8xlarge
    $10.00
    ml.c5.18xlarge
    $10.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Input:

    The algorithm works with numerical data only.

    • Mandatory fields: ‘Time’, ‘Amount’, ‘Class’
    • Class takes values 0 and 1. 1 for fraudulent transactions and 0 for non-fraudulent transactions
    • Time takes integer value and is time of transaction. Time of 1st transaction is 0. Time for other transactions is time elapsed in seconds between 1st transaction and the said transaction
    • Amount is amount of transaction
    • Input file size should not exceed 5 mb.
    • Supported content types : 'text/csv'

    Output:

    • The algorithm returns original data along with 'pred_y' column as predicted class.
    • Supported content types: 'text/csv'

    Invoking endpoint:

    If you are using real time inferencing, please create the endpoint first and then use the following command to invoke it:

    aws sagemaker-runtime invoke-endpoint --endpoint-name "endpoint-name" --body fileb://input.csv --content-type text/csv --accept text/csv out.csv

    Substitute the following parameters:

    • "endpoint-name" - name of the inference endpoint where the model is deployed
    • input.csv - input image to do the inference on
    • text/csv - MIME type of the given input file (above)
    • out.csv - filename where the inference results are written to

    Resources:

    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

    Mphasis DeepInsights Card Fraud Analyzer

    For any assistance reach out to us at:

    AWS Infrastructure

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    Refund Policy

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