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EP 17 | Duke ML for PMs: The Modeling Process episode artwork

Feb 13, 2026 15 min

EP 17 | Duke ML for PMs: The Modeling Process

from AI Bites: The Academic Series Hosted by Jack Lakkapragada

Building a model is about more than just data—it’s about a repeatable process. This episode walks through the lifecycle of a machine learning project, focusing on the strategic decisions a Product Manager must navigate to ensure a model is production-ready. Key Topics: The 5-Step Process: From problem definition and data collection to model evaluation. Feature & Algorithm Selection: How PMs influence which data is used and which model "flavor" fits the business goal. The Bias-Variance Tradeoff: Understanding model complexity so you can troubleshoot "underfitting" or "overfitting" with your engineering team. Validation & Testing: Why we use separate sets to prove a model actually works before it hits the real world. Cross-Validation: Ensuring your model’s performance isn't just a fluke of the data. Note: This is an AI-generated study resource created via NotebookLM based on Duke University’s ML for Product Managers curriculum and personal study notes.

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This episode was published on February 13, 2026.

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