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Artificial Intelligence with Power BI

You're reading from   Artificial Intelligence with Power BI Take your data analytics skills to the next level by leveraging the AI capabilities in Power BI

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801814638
Length 348 pages
Edition 1st Edition
Languages
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Author (1):
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Mary-Jo Diepeveen Mary-Jo Diepeveen
Author Profile Icon Mary-Jo Diepeveen
Mary-Jo Diepeveen
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Table of Contents (18) Chapters Close

Preface 1. Part 1: AI Fundamentals
2. Chapter 1: Introducing AI in Power BI FREE CHAPTER 3. Chapter 2: Exploring Data in Power BI 4. Chapter 3: Data Preparation 5. Part 2: Out-of-the-Box AI Features
6. Chapter 4: Forecasting Time-Series Data 7. Chapter 5: Detecting Anomalies in Your Data Using Power BI 8. Chapter 6: Using Natural Language to Explore Data with the Q&A Visual 9. Chapter 7: Using Cognitive Services 10. Chapter 8: Integrating Natural Language Understanding with Power BI 11. Chapter 9: Integrating an Interactive Question and Answering App into Power BI 12. Chapter 10: Getting Insights from Images with Computer Vision 13. Part 3: Create Your Own Models
14. Chapter 11: Using Automated Machine Learning with Azure and Power BI 15. Chapter 12: Training a Model with Azure Machine Learning 16. Chapter 13: Responsible AI 17. Other Books You May Enjoy

Getting insights with Computer Vision using AI Insights

The easiest way to analyze images in Power BI is by using the Computer Vision model provided to us through the AI Insights feature in Power BI. The AI Insights feature in Power BI does exactly the same as the Computer Vision API from Azure's Cognitive Services.

When we use a pretrained Computer Vision model such as the one offered by Cognitive Services and AI Insights, we don't have to provide any training dataset and can use the model to analyze our images.

Using a pretrained model brings with it advantages and disadvantages. As already discussed in Chapter 7, Using Cognitive Services, the purpose of these pretrained models is to reduce the time and expertise needed by someone such as you to apply them. However, pretrained models are often trained on a generic dataset, which makes them applicable to many different situations.

It may be of course that for your specific use case, using a pretrained model doesn...

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