Pluralsight Course Published – Designing an Intelligent Edge in Microsoft Azure

Designing an Intelligent Edge in Microsoft Azure was just published on Pluralsight! Check it out. Here is a synopsis of what’s in it:

This course targets software developers that are looking to integrate AI solutions in edge scenarios ranging from an edge data center down to secure microcontrollers. This course will showcase how to design solutions using Microsoft Azure.

Cloud computing has moved more and more out of the cloud and onto the edge. In this course, Designing an Intelligent Edge in Microsoft Azure, you will learn foundational knowledge of edge computing, its intersection with AI, and how to utilize both with Microsoft Azure. First, you will learn the concepts of edge computing. Next, you will discover how to create an edge solution utilizing Azure Stack, Azure Data Box Edge, and Azure IoT Edge. Finally, you will explore how to utilize off the shelf AI and build your own for Azure IoT Edge. When you are finished with this course, you will have the skills and knowledge of AI on the edge needed to architect your next edge solution. Software required: Microsoft Azure, .NET

 

Multiple TensorFlow Graphs from Cognitive Services – Custom Vision Service

For one project, there was a need for multiple models within the same Python application. These models were trained using the Cognitive Services: Custom Vision Service. There are two steps to using an exported model:

  1. Prepare the image
  2. Classify the image

Prepare an image for prediction

Classify the image

To run multiple models in Python was fairly simple. Simply call tf.reset_default_graph() after saving the loaded session into memory.

After the CustomVisionCategorizer is create, just call score and it will score with the labels in the map.