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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

Exploring data with R visuals

Power BI has the capability to run R scripts and display R visuals. R is a powerful language that is often used by data scientists for statistics and ML. You will need to install R on your local machine to use it with Power BI Desktop per the instructions at https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-r-visuals.

There are numerous R visualizations that can be useful for data analysis and finding new features for ML models. The FAA Wildlife Strike data contains several True/False flags related to the portions of the aircraft struck, the location of damage, the ingestion of animals into the engines, and more. These values should fit nicely on an R correlation plot, which will graphically show flags that tend to correlate either positively or negatively. Let’s give it a shot!

You will follow three steps to find new features:

  1. Prep are the data for the R correlation plot.
  2. Build the R correlation plot visualization...
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