Best Practices for ML Engineering from Google [pdf]
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Submission timeline
2007–2026One slot for every year since HN launched. Height is that year's peak points; orange marks a 100+ point or 50+ comment breakout. Select a bar to open its strongest thread.
First comments on top threads
HN comment orderAnother good resource from Google is [1] which focuses more on operational impacts after you deploy a system that relies on ML (I'm a coauthor). [2], which was written by my boss, is also great. [1] https://sites.google.com/site/wildml2016nips/SculleyPaper1.p... [2] https://research.google.com/pubs/pub43146.html
These rules are also on Google's Machine Learning Guide[1]. I find the website easy to parse. Definitely an awesome resource to review before jumping into any ML project! [1] https://developers.google.com/machine-learning/guides/rules-...
The first top-level comment from each of the four biggest threads, in HN’s own order. Excerpts are shortened; open a comment for full context.
- Breakout years
- 2
- Total points
- 598
- Total comments
- 20
100+ points or 50+ comments
reference only — not used in Hall rules or ranking
reference only — not used in Hall rules or ranking
Every submission
| Date | Title as submitted | By | Points | Comments |
|---|---|---|---|---|
| 2017-01-10 | Rules of ML [pdf] | Dawny33 | 4 | 0 |
| 2017-01-17 | Best Practices for ML Engineering from Google [pdf]First breakout · Best thread | tim_sw | 406 | 16 |
| 2019-12-13 | Rules of Machine Learning: Best Practices for ML Engineering [pdf]Latest 20+ point return | yarapavan | 188 | 4 |