Hosted by Lin Jia · 🇺🇸 US · EN · 10 episodes
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Inference & Intelligence Lab is a podcast on statistical inference, causal inference, machine learning, and GenAI evaluation, focused on making decisions that hold up in real-world data science. The show features two series—Causal Inference From the Ground Up and Inference in the Wild—covering both first principles and practical pitfalls.
Lin Jia hosts Inference & Intelligence Lab, a technology show with 10 episodes published.
EP4: Two Ways to Measure Demand, and When the Market Lens Matters "Demand" can mean more than one thing. In day-to-day product analytics, it’s the chart right in front of us: sessions, searches, transactions, and convers
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Across the tech industry, many of the most valuable features rely on voluntary adoption. A traveler chooses whether to join a loyalty program, or a marketplace seller decides whether to opt into a smart-pricing tool. Bec
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EP2: Build the Camera — Why Measurement Design Trumps Statistical Testing Running a statistical test is simply pressing the shutter. But designing the measurement system? That is building the camera. In this episode, we
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No Interference, No Ambiguity: The SUTVA Assumption Your randomized experiment is clean. The groups are balanced and comparable. The p-value is significant. But behind the scenes, the treatment is leaking. User A shared
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No Overlap, No Answer: The Positivity Assumption A causal effect can only be estimated where a comparison is actually possible. Imagine evaluating a loyalty program where every enterprise customer is already enrolled—lea
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Comparing Apples to Apples: The Exchangeability Assumption Your dashboard flags a troubling trend: users who contacted customer support have a 40% higher churn rate than those who didn’t. The immediate takeaway seems obv
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You can never see the data you need most to make a decision. 📉 It sounds counterintuitive, but the core of Causal Inference isn't just math—it's imagination. 🌌 Most Data Science focuses on predicting the future based o
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Headline: Why your "Perfect" Models are failing the Boardroom. For months, the team worked on the model. The AUC was 0.92. The validation sets were clean. But when you shipped it to the real world? Nothing happened. The
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The Infinite Data Trap: Why More Data Won't Save Your Causal Models You have petabytes of user data. Your model has 99% validation accuracy. But when you ask it, "What happens if we change our strategy?", it gives you an
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The Ranking Trap: Why PLR Fails with Multiple Treatments You’re testing four different promotional strategies—a discount, free shipping, BOGO, and loyalty points. You run a Partially Linear Regression (PLR), get a clean
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The Recipe for Causal Truth: Estimand, Estimator, and Estimate You have a dataset, a model, and a final number. But can you explain—with precision—what that number actually represents? In the world of causal inference, p
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Inference & Intelligence Lab is hosted by Lin Jia. The show is categorised under technology and has published 10 episodes.
Inference & Intelligence Lab has published 10 episodes.
Inference & Intelligence Lab regularly covers technology. It sits in the technology category.
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