AI-900: Microsoft Azure AI Fundamentals Study Guide
This comprehensive study guide provides a thorough overview of the topics covered in the Microsoft Azure AI Fundamentals (AI-900) exam, including Artificial Intelligence workloads, fundamental principles of machine learning, computer vision and natural language processing workloads. Learn about the exam's intended audience, how to earn the certification, and the skills measured as of April 2022. Discover the important considerations for responsible AI, the capabilities of Azure Machine Learning Studio and more. Get ready to demonstrate your knowledge of AI and ML concepts and related Microsoft Azure services with this helpful study guide.Microsoft Learn AI Skills Challenge
Join Microsoft's AI Skills Challenge 2023 to enhance your technical expertise in Artificial Intelligence. Register now to access exclusive resources, hands-on labs, and interactive learning sessions. Boost your knowledge in generative AI, machine learning, cognitive services, natural language processing, and computer vision to stay ahead in the ever-evolving world of AI.Make Azure AI Real: Apply Azure AI Services for Vision and Florence to your image data
You might have heard a lot about the advancements of generative AI in the NLP domain, but generative AI also heavily enhanced computer vision, enabling models that perform image captioning, editing, retrieval and even generation with the highest accuracy we’ve ever seen.AI Show - Applied AI: Computer Vision and Optical Character Recognition
Computer vision is one the core areas of artificial intelligence and can empower your AI-enabled solution to ‘see’ the world and turning it in a readable/audible experience. Join the next AI show episode on August 26th to learn how to integrate the power of Azure computer vision service in a static web app and how to deploy and run it on the cloud.Build, train, and evaluate an object detection model using ComputerVision Recipes
In this article, we will show how to build, train, and evaluate an object detection model in just a few lines of code using the open-source Computer Vision Recipes repository. The repository supports various scenarios, including classification, retrieval, segmentation, detection, tracking, and action recognition.
