Computer vision in machine learning has allowed us to tell if there are accidents on roads or unsafe work environments and can be used in conjunction with complex systems such as smart sales assistants. Computer vision has opened up many possibilities in IoT. Computer vision is also one of the most challenging from a cost perspective. In the next two recipes, we are going to discuss two different ways of using computer vision. The first one takes in large amounts of images generated from IoT devices and performs predictions and analysis on them using the high-performance distributed Databricks format. In the next recipe, we are going to use a technique for performing machine learning on edge devices with a small amount of compute using a low compute algorithm.
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You're reading from Artificial Intelligence for IoT Cookbook
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