
Understanding Machine Learning: A Friendly, No-Math Guide to How Computers Learn, Make Predictions, and Shape Everyday Life
Thomas Kessler
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Opening Credits
1/14/2026
Chapter 1: When Machines Seem To Think
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Chapter 2: Data The Raw Material Of Machine Learning
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Chapter 3: From Messy Reality To Useful Clues Features And Representations
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Chapter 4: Models As Habitual Guessers How Machines Form Hunches
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Chapter 5: Practice Makes Better Training And Learning From Examples
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Chapter 6: Teaching With Answers Supervised Learning In Daily Life
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Chapter 7: Learning Without A Teacher Unsupervised And Hidden Patterns
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Chapter 8: Trial And Error Learning Reinforcement And Decision Making Over Time
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Chapter 9: When Machines Misjudge Evaluation Failure Bias And Real World Consequences
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Chapter 10: Living With Learning Machines Today And Tomorrow
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Closing Credits
1/14/2026