Deployment of the model can be different depending on the capabilities of the device. Some devices with extra compute can handle having the machine learning models run directly on the device. While others require assistance. In this chapter, we are going to deploy the model to a simple web service. With modern cloud web apps or Kubernetes these web services can scale to meet the needs of the fleet of devices. In the next chapter, we will show how to run the model on the device.
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Michael Roshak is a cloud architect and strategist with extensive subject matter expertise in enterprise cloud transformation programs and infrastructure modernization through designing, and deploying cloud-oriented solutions and architectures. He is responsible for providing strategic advisory for cloud adoption, consultative technical sales, and driving broad cloud services consumption with highly strategic accounts across multiple industries.
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Michael Roshak is a cloud architect and strategist with extensive subject matter expertise in enterprise cloud transformation programs and infrastructure modernization through designing, and deploying cloud-oriented solutions and architectures. He is responsible for providing strategic advisory for cloud adoption, consultative technical sales, and driving broad cloud services consumption with highly strategic accounts across multiple industries.
Read more about Michael Roshak