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Probability in AI: A Friendly, Practical Introduction to Uncertainty, Bayes, and Decision-Making for Modern Machine Learning-logo

Probability in AI: A Friendly, Practical Introduction to Uncertainty, Bayes, and Decision-Making for Modern Machine Learning

Luca Benedetti

Master the language of uncertainty to build robust machine learning models and drive smarter artificial intelligence. Whether you are upskilling during a commute or diving into focused study, this guide transforms complex math into practical tools....

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Opening Credits

1/13/2026
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Chapter 1: Why AI Needs Probability

1/13/2026
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Chapter 2: From Uncertainty to Random Variables

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Chapter 3: Distributions The Shapes of Uncertainty

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Chapter 4: Conditional Probability Seeing the World in Context

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Chapter 5: Bayes Rule Updating Beliefs the AI Way

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Chapter 6: Building Simple Probabilistic Models Naive Bayes and Friends

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Chapter 7: Likelihood and Learning from Data

1/13/2026
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Chapter 8: How Sure Is the Model Uncertainty and Calibration in ML

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Chapter 9: Decisions Under Uncertainty Costs, Risks, and Trade Offs

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Chapter 10: Probability and Modern ML From Deep Nets to Everyday Practice

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Closing Credits

1/13/2026