Session
Adding Intelligence: Unlocking New Insights with AI and Machine Learning
with Akanksha Malik
For many scenarios, the cloud is used as a way to process data and apply business logic with nearly limitless scale. However, processing data in the cloud is not always the optimal way to run computational workloads: either because of connectivity issues, legal concerns, or because you need to respond in near-real time with processing at the Edge.
In this session we dive into how Azure IoT Edge can help in this scenario. We will train a machine learning model in the cloud using the Azure AI Platform and deploy this model to an IoT Edge device using Azure IoT Hub.
At the end, you will understand how to develop and deploy AI and ML workloads at the Edge.
Check out more on Microsoft Learn!
For many scenarios, the cloud is used as a way to process data and apply business logic with nearly limitless scale. However, processing data in the cloud is not always the optimal way to run computational workloads: either because of connectivity issues, legal concerns, or because you need to respond in near-real time with processing at the Edge.
In this session we dive into how Azure IoT Edge can help in this scenario. We will train a machine learning model in the cloud using the Azure AI Platform and deploy this model to an IoT Edge device using Azure IoT Hub.
At the end, you will understand how to develop and deploy AI and ML workloads at the Edge.
Check out more on Microsoft Learn!
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