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.
Synthetic Tabular Data Generator
Latest Version:
1.3.2
A generative algorithm based solution to produce synthetic tabular data
Product Overview
This solution efficiently creates high-quality tabular synthetic data. It empowers businesses and researchers to overcome data scarcity, privacy, and compliance challenges by generating realistic and representative synthetic datasets. It maintains the statistical properties, correlations, and patterns of the original data, ensuring the output remains useful and relevant for your use case. The synthetic data generator supports a wide range of data types, including numerical, categorical, and datetime variables, allowing you to generate synthetic data tailored to your specific needs.
Key Data
Version
Type
Model Package
Highlights
The Synthetic Tabular Data Generataor uses generative adversarial networks to create synthetic data that accurately mimics the statistical properties of real data without revealing sensitive information, enabling compliance with GDPR, HIPAA, and other privacy regulations. Its efficient implementation ensures rapid generation of large-scale synthetic data, helping users save time and resources.
This solution can be used by businesses, data science teams and software testing teams in various industries like healthcare, finance, retail, HR & workforce insurance and smart cities etc to complement their existing data scources in a reliable and privacy preserving manner.
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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 Batch Transform$300.00/hr
running on ml.m5.large
Infrastructure PricingWith 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
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 Batch Transform$0.115/host/hr
running on ml.m5.large
Model Batch Transform
For model deployment as Batch transform job 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 | Batch Transform/hr | |
|---|---|---|
ml.m4.4xlarge | $300.00 | |
ml.m5.4xlarge | $300.00 | |
ml.m4.16xlarge | $300.00 | |
ml.m5.2xlarge | $300.00 | |
ml.p3.16xlarge | $300.00 | |
ml.m4.2xlarge | $300.00 | |
ml.c5.2xlarge | $300.00 | |
ml.p3.2xlarge | $300.00 | |
ml.c4.2xlarge | $300.00 | |
ml.m4.10xlarge | $300.00 | |
ml.c4.xlarge | $300.00 | |
ml.m5.24xlarge | $300.00 | |
ml.c5.xlarge | $300.00 | |
ml.p2.xlarge | $300.00 | |
ml.m5.12xlarge | $300.00 | |
ml.p2.16xlarge | $300.00 | |
ml.c4.4xlarge | $300.00 | |
ml.m5.xlarge | $300.00 | |
ml.c5.9xlarge | $300.00 | |
ml.m4.xlarge | $300.00 | |
ml.c5.4xlarge | $300.00 | |
ml.p3.8xlarge | $300.00 | |
ml.m5.large Vendor Recommended | $300.00 | |
ml.c4.8xlarge | $300.00 | |
ml.p2.8xlarge | $300.00 | |
ml.c5.18xlarge | $300.00 |
Usage Information
Model input and output details
Input
Summary
The model take two files in a zipped file.
- A config file (config.txt) with two parameters
- "length_of_sample" : number of records to be generated (an integer)
- "categorical column": a comma separated list of column hearders in the sample csv file to be designated as categorical data type and treated as such during data generation
- A csv file containing the representative sample data to be used as a reference for synthetic data generation
Limitations for input type
Realtime inferencing is not supported due to the nature of use-case
Input MIME type
application/zipSample input data
Output
Summary
A csv table with the synthetically generated data
Output MIME type
text/csvSample output data
Sample notebook
Additional Resources
End User License Agreement
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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.
Learn MoreRefund Policy
We do not provide any usage related refunds at this time.
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