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.
Automobile Carbon Footprint Prediction
Latest Version:
1.0.2
This solution predicts the running carbon footprint of a car
Product Overview
How green is your car? Cars running on hyrocarbon based fuels are a major contributor of greenhouse gasses in the atmosphere. With the sustainability becoming a decision criteria of acquiring a car along with the other usual attributes like performance, asthetics, reliability etc, this solution provides a simple way of ascertaining the running carbon footprint of the car. The solution uses supervised machine learning approch to predict the carbon dioxide (CO2) emission in kg per mile of running of a vehicle in standard conditions. The solution uses vehicle's dimensions, transmission, manufactured year, gears, horsepower, drive etc. to predict the fuel consumption and the carbon emission of the vehicle.
Key Data
Version
Categories
Type
Model Package
Highlights
The machine learning solution can analyze various car attributes like engine size, fuel type, vehicle weight, and more to provide precise predictions of the car's carbon footprint and mileage. This helps car owners and potential buyers make informed decisions based on the environmental impact and fuel efficiency of the vehicle.
The machine learning solution can be integrated with various platforms and tools, making it easy for users to access and understand the predictions. This may include interactive dashboards, mobile applications, or integration with car dealership websites, allowing users to visualize and compare the carbon footprint and mileage of different vehicles easily.
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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.
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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$5.00/hr
running on ml.t2.medium
Model Batch Transform$10.00/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 Realtime Inference$0.056/host/hr
running on ml.t2.medium
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
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.r5.large | $5.00 | |
ml.r6g.xlarge | $5.00 | |
ml.r6g.2xlarge | $5.00 | |
ml.c5.large | $5.00 | |
ml.r6g.large | $5.00 | |
ml.m4.xlarge | $5.00 | |
ml.m5d.2xlarge | $5.00 | |
ml.c5.2xlarge | $5.00 | |
ml.c4.large | $5.00 | |
ml.r5.xlarge | $5.00 | |
ml.c4.2xlarge | $5.00 | |
ml.t2.xlarge | $5.00 | |
ml.c4.xlarge | $5.00 | |
ml.m5d.xlarge | $5.00 | |
ml.m5d.large | $5.00 | |
ml.c5.xlarge | $5.00 | |
ml.t2.large | $5.00 | |
ml.r5.2xlarge | $5.00 | |
ml.t2.medium Vendor Recommended | $5.00 |
Usage Information
Model input and output details
Input
Summary
The input data must be in json format.
Input MIME type
application/jsonSample input data
Output
Summary
The output file contains the average mileage predicted column(MPG), carbon footprint (kg/km) along with the input features.
Output MIME type
text/csv, 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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