Building Object Detectors with Azure Custom Vision

Computer vision is transforming how businesses process visual data, but you do not need a PhD in machine learning to build powerful image recognition tools. By leveraging cloud-based services, you can design, train, and deploy custom object detection models quickly and efficiently. This text-only course guides you through the entire lifecycle of creating an object detector using the Azure Custom Vision web portal. You will learn how to structure your image datasets, annotate objects accurately, train models, and evaluate their performance using modern industry metrics. What you'll learn: 1. Understand foundational computer vision concepts and object detection terminology. 2. Prepare and organize a balanced image dataset for training. 3. Tag and annotate objects of interest using the Azure Custom Vision web portal. 4. Train custom models and interpret key evaluation metrics like precision, recall, and mAP. 5. Test your trained models using sample images and refine their performance. 6. Explore how to integrate your trained object detector into applications via REST APIs. You will start with the fundamental concepts of computer vision before moving step-by-step through dataset preparation, annotation, model training, and testing. The course concludes with practical guidance on deploying your model for real-world application integration. This course is designed for beginners, software developers, and cloud enthusiasts looking to add computer vision capabilities to their projects. No prior machine learning or programming experience is required. Start reading today to build your first custom object detection model in the cloud.