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.
Propensity US: Macy's Clothing Shopper
Latest Version:
V 1.0
Propensity model that determines the probability that a consumer is Macy's Clothing Shopper
Product Overview
Prosper Insights & Analytics' propensity model predicts the probability that a U.S. adult consumer is a Macy's Clothing Shopper. Based on a set of basic demographics, the model identifies individuals likely to be a Macy's Clothing Shopper. The model was trained with data from Prosper's large database of U.S. adult consumer intentions and actions.
Key Data
Version
Type
Model Package
Highlights
Enhances digital and offline targeting by identifying individuals likely to be a Macy's Clothing Shopper
100% Privacy Compliant Models. No PII Used.
Based on unique large sample consumer survey data
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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.
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 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 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.m4.4xlarge | $0.00 | |
ml.m5.4xlarge | $0.00 | |
ml.m4.16xlarge | $0.00 | |
ml.p3.16xlarge | $0.00 | |
ml.m5.2xlarge | $0.00 | |
ml.m4.2xlarge | $0.00 | |
ml.c5.2xlarge | $0.00 | |
ml.p3.2xlarge | $0.00 | |
ml.c4.2xlarge | $0.00 | |
ml.m4.10xlarge | $0.00 | |
ml.c4.xlarge | $0.00 | |
ml.m5.24xlarge | $0.00 | |
ml.c5.xlarge | $0.00 | |
ml.p2.xlarge | $0.00 | |
ml.m5.12xlarge | $0.00 | |
ml.p2.16xlarge | $0.00 | |
ml.c4.4xlarge | $0.00 | |
ml.c5.9xlarge | $0.00 | |
ml.m5.xlarge | $0.00 | |
ml.m4.xlarge Vendor Recommended | $0.00 | |
ml.c5.4xlarge | $0.00 | |
ml.p3.8xlarge | $0.00 | |
ml.c4.8xlarge | $0.00 | |
ml.m5.large | $0.00 | |
ml.p2.8xlarge | $0.00 | |
ml.c5.18xlarge | $0.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
For complete usage instructions, sample data, and sample code, go to: https://github.com/goprosper/prosper-sagemaker-basic-geo.git
End User License Agreement
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Support Information
AWS Infrastructure
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