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.
Vehicle Damage Inspection
Latest Version:
0.1
Classifies vehicle damage images in multiple types
Product Overview
Significant time is spent by auto insurance adjusters to appraise vehicle loss and estimate the final settlement amount. Large volume of minor loss claims consume significant bandwidth of adjusters. A machine learning model can reduce this amount by inspecting and identifying type of damage after car accident.
Key Data
Version
Type
Model Package
Highlights
Multi-class classifier trained car damage images and classifies them as normal images, broken headlight, broken windshield, full front damage.
Such model can be further extended to estimate claim amount based on the damage (with added efforts).
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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.xlarge Vendor Recommended | $0.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Download the Jupyter notebook in "Additional Resources" section and follow readme.txt provided.
Additional 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
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
Since you are not being charged currently for the use of this software there will be no refund of any charges.
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