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 Data Generator Algorithm
Latest Version:
2.1.1
Algorithm based solution to generate synthetic data
Product Overview
With Synthetic Data Generator Algorithm, businesses can quickly generate synthetic data that accurately mimics real-world data patterns, without the privacy risks associated with using real data. In many use cases it is observed that the business does not have enough data for model training or analytics. The solution uses advanced algorithms and statistical models to create synthetic tabular data that is statistically representative of the real data.In this solution flexibility is provided to the user to bring their own data for algorithm training the model to generate synthetic data. This solution is able to learn from real data and generate synthetic data
Key Data
Version
Categories
Type
Algorithm
Highlights
The user can bring in their own sample data and use the algorithm to train a model which then can be used to generate additional synthetic data. The Synthetic Data Generator Algorithm 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
Algorithm Training$300/hr
running on ml.m5.xlarge
Model Realtime Inference$5.00/hr
running on ml.m5.xlarge
Model Batch Transform$300.00/hr
running on ml.m5.xlarge
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 Algorithm Training$0.23/host/hr
running on ml.m5.xlarge
SageMaker Realtime Inference$0.23/host/hr
running on ml.m5.xlarge
SageMaker Batch Transform$0.23/host/hr
running on ml.m5.xlarge
Algorithm Training
For algorithm training 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 | Algorithm/hr | |
|---|---|---|
ml.c5.2xlarge | $300.00 | |
ml.m4.4xlarge | $300.00 | |
ml.m5.4xlarge | $300.00 | |
ml.m5.12xlarge | $300.00 | |
ml.m5.2xlarge | $300.00 | |
ml.m4.10xlarge | $300.00 | |
ml.m5.xlarge Vendor Recommended | $300.00 | |
ml.c5.9xlarge | $300.00 | |
ml.c5.4xlarge | $300.00 | |
ml.m4.2xlarge | $300.00 |
Usage Information
Training
Training dataset is tabular data in CSV format with attribute data types as numeric, categorical or boolean.
Channel specification
Fields marked with * are required
training
*Input modes: File
Content types: text/csv, text/plain, application/json
Compression types: None
Hyperparameters
Fields marked with * are required
intRange
*The first hyperparameter
Type: Integer
Tunable: No
contRange
*The second hyperparameter
Type: Continuous
Tunable: No
categoricalValues
*The third hyperparameter
Type: Categorical
Tunable: No
Model input and output details
Input
Summary
A CSV file with the tabular dataset. A header row is mandatory in the first rwo. Allowed data types are integer, numerical, categorical and boolean.
Input MIME type
text/csvSample input data
Output
Summary
Output is an text/csv file with the synthetically generated tabular data.
Output MIME type
text/plainSample 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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