Sold by: Modjoul
Deployed on AWS
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The heat index model takes temperature & humidity values and calculates heat index which conveys dangers of excessive heat on human body.
Overview
Jump start your ability to understand heat index which conveys the dangers of excessive heat on human body. The heat index takes into account not only science of meteorology, but biology also. The human body sweats to regulate its internal temperature and helps it cool down. When its humid outside sweat evaporation process is not as effective and the body cannot cool down effectively. Depending upon how humid it is, the difference between actual air temperature and heat index can be significant. Leverage the Modjoul Heat Index model to understand the heat index risks in your given location.
Highlights
- Easy-to-use model quickly calculates heat index based upon the temperature and humidity sensor.
- Use to determine heat index for your employees, athletes, elderly, pets, children, or other groups of people for whom you are responsible.
- Easy to use output to help gauge level of outdoor activity on a given day.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Free trial
Try this product free for 14 days according to the free trial terms set by the vendor.
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.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $0.65 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $0.65 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $0.65 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.65 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.65 |
ml.m5.12xlarge Inference (Batch) | Model inference on the ml.m5.12xlarge instance type, batch mode | $0.65 |
ml.m5.24xlarge Inference (Batch) | Model inference on the ml.m5.24xlarge instance type, batch mode | $0.65 |
ml.m4.xlarge Inference (Batch) | Model inference on the ml.m4.xlarge instance type, batch mode | $0.65 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $0.65 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $0.65 |
Dimensions summary
You pay by the hour for the compute instance that runs the Heat Index Model, which detects extreme heat conditions for worker safety. Pricing follows two usage modes: batch inference for scheduled processing of grouped data, and real-time inference for continuous, on-demand predictions. Within each mode, you choose an ML instance type. Options span general-purpose (m5, m4), compute-optimized (c5, c4), and GPU-accelerated (p2, p3) families. Larger instance sizes within a family carry more processing capacity. Your total cost depends on the mode, the instance size selected, and how many host hours you run.
Top-of-mind questions for buyers
One host hour is one hour that a single ML compute instance runs your inference job. Billing counts the running time of the instance you select. If you run more than one instance, each accrues its own host hours. You are charged for the time the instance is active.
Batch mode runs the model on grouped data during scheduled jobs, so you accrue host hours only while the batch job runs. Real-time mode keeps an instance running to serve continuous, on-demand predictions, so you accrue host hours for as long as that endpoint stays active. Both meter by host hour.
Three factors combine: the mode you choose (batch or real-time), the instance type and size, and the number of host hours you run. The hourly rate rises with instance size within a family. Your bill is the hourly rate multiplied by hours run. Stopping an instance stops software host-hour charges.
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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
Buyer Preview Version
Additional details
Inputs
- Summary
Heat Index Model for Buyer Preview version.
- Input MIME type
- text/csv
See Input Summary
See Input Summary
Support
AWS infrastructure support
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