8 - Baseline Thinking

Naked Data Science

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5+ y ago 26:10

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How to evaluate new versus baseline when you already have an existing solution, how to use tracer bullets when there is no existing solution, and how to build accurate intuitions on both data science and business sides.
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챕터

1. 8 - Baseline Thinking (00:00:00)

2. What is Baseline Thinking (00:00:42)

3. When there is a baseline, beat it (00:02:38)

4. How to measure output of new vs. baseline solutions (00:03:32)

5. Also, think about the cost benefit of new vs. baseline (00:05:01)

6. The danger of endless possibilities (00:05:59)

7. Be scientific and unbiased when evaluating solutions (00:07:15)

8. Think trade-offs (00:08:53)

9. Take turns in advocating for both new vs. baseline solutions (00:10:06)

10. When there isn't a baseline, establish it (00:10:29)

11. Shoot tracer bullets first (00:11:21)

12. Discover hidden problems early (00:12:33)

13. Shoot tracer bullets in different directions (00:13:43)

14. Lower your expectations and impose constraints on yourself (00:14:25)

15. Tracer bullets are not supposed to damage the target (00:15:18)

16. Simple, naive, and stupid solutions often give high return on effort (00:16:24)

17. Let go of your ego (00:16:46)

18. Shoot tracer bullets strategically (00:17:44)

19. Self-impose constraints on different levels of complexity (00:18:44)

20. Seeing potential trade-offs between value and complexity (00:19:19)

21. Discussing trade-offs with business is highly valuable and rewarding (00:20:17)

22. Baselines make ideas tangible (00:21:24)

23. Help business build accurate intuitions on data science solutions (00:22:31)

24. Simple baselines might already be good enough (00:23:22)

25. A practical takeaway (00:24:19)

35 에피소드

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8 - Baseline Thinking

Naked Data Science

35 subscribers

published 5+ y ago

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