AI-900: Computer Vision Workloads on Azure
Azure AI Vision, Custom Vision, Face, OCR, Document Intelligence and Video Indexer for the AI-900 exam.
Computer Vision is a field of artificial intelligence that enables machines to "see" and interpret the visual world. Just as humans use their eyes and brain to understand what they see, computer vision systems use cameras, digital images, and machine learning algorithms to process and interpret visual data.
On Azure, Computer Vision is made possible through a series of dedicated cognitive services that allow developers to integrate advanced visual capabilities into their applications without requiring deep machine learning expertise.
Before the advent of deep learning, computer vision systems relied on traditional image processing algorithms: edge detection, color histograms, descriptors like SIFT and HOG. These approaches were effective under controlled conditions but often failed in complex real-world scenarios.
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What's inside
16 sections- 1 Table of Contents
- 2 Introduction to Computer Vision
- 3 Computer Vision Capabilities on Azure
- 4 Azure AI Vision – In-Depth Image Analysis
- 5 Custom Vision – Building Custom Models
- 6 Azure AI Face – Facial Detection and Recognition
- 7 OCR – Read OCR Engine in Detail
- 8 Azure AI Document Intelligence
- 9 Azure Video Indexer
- 10 Practical Implementation with the Python SDK
- 11 Architecture and Deployment Considerations
- 12 Security, Ethics, and Responsible AI
- 13 Exam Tips and Common Pitfalls
- 14 Practical Exercises and Scenarios
- 15 Summary and Key Points
- 16 Glossary
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