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Power Platform and the AI Revolution

Power Platform and the AI Revolution

By : Aaron Guilmette
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Power Platform and the AI Revolution

Power Platform and the AI Revolution

5 (6)
By: Aaron Guilmette

Overview of this book

In this AI era, employing leading machine learning and AI models such as ChatGPT for responding to customer feedback and prototyping applications is crucial to drive business success in the competitive market. This book is an indispensable guide to integrating cutting-edge technology into business operations and leveraging AI to analyze sentiment at scale, helping free up valuable time to enhance customer relationships. Immerse yourself in the future of AI-enabled application development by working with Power Automate, Power Apps, and the new Copilot Studio. With this book, you’ll learn foundational AI concepts as you explore the extensive capabilities of the low-code Power Platform. You’ll see how Microsoft's advanced machine learning technologies can streamline common business tasks such as extracting key data elements from customer documents, reviewing customer emails, and validating passports and drivers’ licenses. The book also guides you in harnessing the power of generative AI to expedite tasks like creating executive summaries, building presentations, and analyzing resumes. You’ll build apps using natural language prompting and see how ChatGPT can be used to power chatbots in your organization. By the end of this book, you’ll have charted your path to developing your own reusable AI automation patterns to propel your business operations into the future.
Table of Contents (16 chapters)
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What is computer vision?

Azure Computer Vision is a Microsoft cloud service for analyzing images and extracting insights using AI algorithms and deep learning models. Computer Vision can be used to perform a number of image analysis and processing tasks. Azure Computer Vision has a number of different capabilities, including:

  • Image classification: This refers to classifying an image as a whole by identifying the main objects in the content. For example, you might train a model to identify images such as Figure 11.1 using the word “dog.”
Figure 11.1 – Classifying an image as a dog

Figure 11.1 – Classifying an image as a dog

  • Object detection: Similar to image classification, object detection is used to identify objects inside of an image. Objects are indicated through the use of a type of border called a bounding box. Object detection can typically identify different kinds of objects in a single image, as shown in Figure 11.2.
Figure 11.2 – Detecting objects in an image

Figure...

Visually different images
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Power Platform and the AI Revolution
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