Sold by: Prosper Insights & Analytics
Deployed on AWS
Propensity model that determines the probability that a consumer is Planning to Buy a Car or Truck
Overview
This Pandemic Propensity Model determines the probability that a US adult is Planning to Buy a Car or Truck. Lift over Random 1.68
This Pandemic Propensity model is one of a series of consumer classification models based on data from over 24,000 US adults surveyed between April to June 2020 from Prosper's US Monthly Consumer survey. Survey data was collected during the Covid-19 Coronavirus Pandemic, capturing behavior changes and preferences during the National Emergency. The survey is anonymous. Zero PII. CCPA and HIPAA Compliant.
Highlights
- Enhances digital and offline targeting by identifying an individual’s probability to engage in a specific behavior. Model is based on data from over 24.000 US adults surveyed between April to July 2020 from Prosper's US Monthly Consumer survey.
- 100% Privacy Compliant Models. No PII Used.
- Lift over Random 1.68
Details
Sold by
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m4.xlarge Inference (Batch) Recommended | Model inference on the ml.m4.xlarge instance type, batch mode | $350.00 |
ml.m4.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m4.xlarge instance type, real-time mode | $0.28 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $350.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $350.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $350.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $350.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $350.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $350.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $350.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $350.00 |
Dimensions summary
You pay by the host hour for running this predictive model on AWS SageMaker infrastructure. Pricing splits into two modes: Batch, which processes grouped data in scheduled runs, and Real-Time, which serves predictions on demand. Within each mode, you choose an instance type. Options span general-purpose (m4, m5), compute-optimized (c4, c5), and GPU-accelerated (p2, p3) families, in sizes from large through 24xlarge. Larger instances and GPU types carry different hourly rates. You are billed only for the hours each instance runs, so cost scales with the size and runtime you select.
Top-of-mind questions for buyers
One host hour is one hour that a single chosen instance runs the model. If you run one instance for four hours, you are billed four host hours. Running multiple instances at once multiplies the hours accrued during that period.
Both meter host hours. Batch mode runs the model over grouped data in scheduled jobs, so you pay for the hours a job takes. Real-Time mode keeps an instance running to serve on-demand predictions, so hours accrue for as long as the endpoint stays active.
Yes. Host hours accrue for every hour an instance stays active, whether or not it processes predictions. To stop software charges, you must shut the endpoint down. Batch jobs meter only while the job runs, so idle time between scheduled runs does not accrue hours.
www.prospermodelfactory.com
Helpful?
Vendor refund policy
No refunds
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
None
Additional details
Inputs
- Summary
For complete usage instructions, sample data, and sample code, go to: https://github.com/goprosper/prosper-sagemaker-basic-geo.git
- Input MIME type
- text/csv
See Input Summary
See Input Summary
Support
AWS infrastructure support
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.
Similar products
Propensity model that determines the probability that a consumer is Planning to Buy a House.
Propensity model that determines the probability that a consumer is Planning to Buy Furniture.
Propensity model that determines the probability that a consumer is Planning to Buy a Computer
Propensity model that determines the probability that a consumer is Planning Vacation Travel.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.