
Predictive Modeling With AI: A Practical Guide to Building, Evaluating, and Deploying Data-Driven Forecasts
Eric Donnelly
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Opening Credits
1/13/2026
Chapter 1: From Gut Feel To Predictive Modeling
1/13/2026
Chapter 2: Framing The Right Prediction Problem
1/13/2026
Chapter 3: Working With Real World Data
1/13/2026
Chapter 4: Designing Features That Capture Signal
1/13/2026
Chapter 5: Choosing The Right Model Family
1/13/2026
Chapter 6: Training Models Without Fooling Yourself
1/13/2026
Chapter 7: Measuring What Matters With Model Metrics
1/13/2026
Chapter 8: Tackling Imbalanced, Temporal, And Drifting Data
1/13/2026
Chapter 9: Making Models Understandable, Fair, And Governed
1/13/2026
Chapter 10: From Prototype To Production And Beyond
1/13/2026
Closing Credits
1/13/2026