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AI & Data Literacy

You're reading from   AI & Data Literacy Empowering Citizens of Data Science

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Product type Paperback
Published in Jul 2023
Publisher
ISBN-13 9781835083505
Length 238 pages
Edition 1st Edition
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Author (1):
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Bill Schmarzo Bill Schmarzo
Author Profile Icon Bill Schmarzo
Bill Schmarzo
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Table of Contents (14) Chapters Close

Preface 1. Why AI and Data Literacy? FREE CHAPTER 2. Data and Privacy Awareness 3. Analytics Literacy 4. Understanding How AI Works 5. Making Informed Decisions 6. Prediction and Statistics 7. Value Engineering Competency 8. Ethics of AI Adoption 9. Cultural Empowerment 10. ChatGPT Changes Everything 11. Glossary 12. Other Books You May Enjoy
13. Index

Understanding the Confusion Matrix

The previous chapter discussed the Decision Matrix and Pugh Matrix to help us make informed decisions. The next step beyond Decision Matrix and Pugh Matrix is the Confusion Matrix, a most aptly named statistical construct. A Confusion Matrix is used to evaluate the performance of an AI / ML model by comparing the predicted results with the actual results. The matrix shows the number of true positive, true negative, false positive, and false negative predictions made by the model. In other words, it shows the number of correct and incorrect predictions made by the model. It can be used to calculate a variety of AI / ML model performance metrics, such as precision, recall, and accuracy, which can help to identify the strengths and weaknesses of the AI / ML model.For example, let’s say I’m a shepherd, and my job is to correctly distinguish between my sheepdog protecting my sheep and a wolf out to eat my sheep. Unfortunately, I have bad eyesight...

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