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Pluralsight

Building Features for Computer Vision in Microsoft Azure

via Pluralsight

Overview

This course will cover how to leverage both an algorithmic as well as a deep learning approach for building features from image data on Microsoft Azure.

Computer vision enables insights and experiences that previously weren’t possible, but it can seem daunting to know how to extract the information you need out of an image. In this course, Building Features from Image Data in Microsoft Azure, you will learn how to leverage the tools and services provided by Microsoft Azure alongside popular computer vision and deep learning frameworks to extract relevant information from images. First, you will explore computer vision, its use cases, and also take a look at what Azure provides to make this easier for you. Next, you will learn about the algorithmic approach to computer vision by reviewing popular feature descriptors like the scale-invariant feature transform and the histogram of oriented gradients. Finally, you will delve into deep learning as a tool to leverage in computer vision by creating a convolutional neural network to classify images. When you are finished with this course, you will have both the knowledge and tools to build features out of your image data on Microsoft Azure.

Topics:
  • Course Overview
  • Exploring Computer Vision on Azure
  • Utilizing the SIFT and HOG Algorithms for Feature Detection
  • Leveraging Convolutional Neural Networks for Feature Extraction

Taught by

David Tucker

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