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Power BI Machine Learning and OpenAI

You're reading from   Power BI Machine Learning and OpenAI Explore data through business intelligence, predictive analytics, and text generation

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781837636150
Length 308 pages
Edition 1st Edition
Languages
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Author (1):
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Greg Beaumont Greg Beaumont
Author Profile Icon Greg Beaumont
Greg Beaumont
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Data Exploration and Preparation
2. Chapter 1: Requirements, Data Modeling, and Planning FREE CHAPTER 3. Chapter 2: Preparing and Ingesting Data with Power Query 4. Chapter 3: Exploring Data Using Power BI and Creating a Semantic Model 5. Chapter 4: Model Data for Machine Learning in Power BI 6. Part 2: Artificial Intelligence and Machine Learning Visuals and Publishing to the Power BI Service
7. Chapter 5: Discovering Features Using Analytics and AI Visuals 8. Chapter 6: Discovering New Features Using R and Python Visuals 9. Chapter 7: Deploying Data Ingestion and Transformation Components to the Power BI Cloud Service 10. Part 3: Machine Learning in Power BI
11. Chapter 8: Building Machine Learning Models with Power BI 12. Chapter 9: Evaluating Trained and Tested ML Models 13. Chapter 10: Iterating Power BI ML models 14. Chapter 11: Applying Power BI ML Models 15. Part 4: Integrating OpenAI with Power BI
16. Chapter 12: Use Cases for OpenAI 17. Chapter 13: Using OpenAI and Azure OpenAI in Power BI Dataflows 18. Chapter 14: Project Review and Looking Forward 19. Index 20. Other Books You May Enjoy

Use Cases for OpenAI

In the previous chapter, you scored fresh data via the Power BI ML models and assessed the output in comparison to the automated testing performed by Power BI during the training phase. The FAA Wildlife Strike database provided fresh data that was generated in the real world beyond the scope of the training and testing datasets. This data could potentially serve as a framework for scheduling the scoring of new data utilizing a Power BI ML model in collaboration with dataflows. The recently evaluated data produced outcomes that were relatively consistent with the expected results derived from the testing data.

In this chapter, you are tasked by your stakeholders to incorporate OpenAI functionalities into the solution. OpenAI is garnering a lot of attention in the IT sector, and this project is being implemented during this trend. Although this entails a change in scope, the project’s beneficiaries are fully supportive of and optimistic about this initiative...

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