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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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Natural Language Sentence Generator

Latest Version:
3.5
The solution generates new text data from existing data using data augmentation at sentence level.

    Product Overview

    Natural Language Sentence Generator helps ML practitioners to significantly increase the diversity of data available for training models, without actually collecting new data. The effectiveness of machine learning based classifiers largely depends on the size and quality of the training data. This solution helps to increase the size of the dataset and introduce variability in the dataset.

    Key Data

    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • The solution can be leveraged to augment text data at sentence level to generate new data with similar context from input sample.

    • The solution generates additional text data from limited textual datasets and thereby solve class imbalance problem.

    • PACE - ML is Mphasis Framework and Methodology for end-to-end machine learning development and deployment. PACE-ML enables organizations to improve the quality & reliability of the machine learning solutions in production and helps automate, scale, and monitor them. Need customized Machine Learning and Deep 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$8.00/hr

    running on ml.m5.large

    Model Batch Transform$16.00/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
    $8.00
    ml.m5.4xlarge
    $8.00
    ml.m4.16xlarge
    $8.00
    ml.m5.2xlarge
    $8.00
    ml.p3.16xlarge
    $8.00
    ml.m4.2xlarge
    $8.00
    ml.c5.2xlarge
    $8.00
    ml.p3.2xlarge
    $8.00
    ml.c4.2xlarge
    $8.00
    ml.m4.10xlarge
    $8.00
    ml.c4.xlarge
    $8.00
    ml.m5.24xlarge
    $8.00
    ml.c5.xlarge
    $8.00
    ml.p2.xlarge
    $8.00
    ml.m5.12xlarge
    $8.00
    ml.p2.16xlarge
    $8.00
    ml.c4.4xlarge
    $8.00
    ml.m5.xlarge
    $8.00
    ml.c5.9xlarge
    $8.00
    ml.m4.xlarge
    $8.00
    ml.c5.4xlarge
    $8.00
    ml.p3.8xlarge
    $8.00
    ml.m5.large
    Vendor Recommended
    $8.00
    ml.c4.8xlarge
    $8.00
    ml.p2.8xlarge
    $8.00
    ml.c5.18xlarge
    $8.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Input:

    Following are the mandatory inputs guidelines: • The input csv should have a column named as "sentence" which contains the sentences • Supported content types: text/csv.

    Output:

    Instructions for output interpretation: • Output will be the augmented sentences with 3 predictions. • Output content type: A “.csv” file with the instances. • 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://sample.csv --content-type text/csv --accept text/csv out.csv

    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

    Natural Language Sentence Generator

    For any assistance reach out to us at:

    AWS Infrastructure

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    Refund Policy

    Currently we do not support refunds, but you can cancel your subscription to the service at any time.

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