Azure AI Engineer Certification | Microsoft Azure AI Online
                     Implementing AI for Vision-Based 
Applications in Azure
Subtitle: Leveraging Azure AI Services 
for Intelligent Vision Solutions
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Introduction to Vision-Based AI
• Vision-based AI enables machines to 
interpret and process visual data.
• Common use cases: facial recognition, 
object detection, OCR, image 
classification.
• Azure offers robust tools and services for 
developing and deploying vision 
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Azure AI Tools for Vision
• Azure Computer Vision: Extracts 
information from images and videos.
• Custom Vision: Train custom image 
classification and object detection models.
• Face API: Detects and recognizes human 
faces.
• Form Recognizer: Extracts text, key-
value pairs, and tables from documents.
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Architecture Overview
• Data Ingestion: Upload via Azure Blob Storage or Azure 
Data Factory.
• Preprocessing: Azure Functions or 
Azure Machine Learning for image resizing, cleaning.
• Model Training: Use Azure Custom Vision or Azure 
Machine Learning.
• Deployment: Host model with Azure Kubernetes Service or 
Azure App Services.
• Monitoring: Use Azure Monitor and Application Insights.
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Using Azure Computer Vision
• Detect objects, read 
printed/handwritten text (OCR), and 
generate image descriptions.
• REST API or SDK available in 
multiple programming languages.
• Integrates easily with Logic Apps 
and Power Automate.
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Building with Custom Vision
• Upload labeled images via UI or API.
• Train and test models for classification or 
object detection.
• Export models for edge deployment or use 
them via REST API.
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Face API for Facial Recognition
• Detect face attributes (age, 
emotion, landmarks).
• Compare and verify faces.
• Secure identity solutions with face 
authentication.
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Integration with Other Azure Services
• Azure Cognitive Search for indexing visual 
data.
• Power BI for visual insights.
• Azure IoT Edge for deploying vision 
models to edge devices.
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Conclusion and Best Practices
• Start with prebuilt models, move to 
custom models as needed.
• Ensure ethical AI use: privacy, bias 
mitigation.
• Leverage Azure’s scalability, 
security, and compliance for 
enterprise-grade solutions.
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For More Information About 
Azure AI Engineer
Address:- Flat no: 205, 2nd Floor,
   Nilagiri Block, Aditya Enclave,  Ameerpet, 
Hyderabad-16
   Ph. No: +91-998997107
  www.visualpath.in
    [email protected]
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Thank You
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