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| Best Practices for ML Engineering from Google [pdf] (martin.zinkevich.org) | ||
| recommended by 2 users | 2017 | 406 points by tim_sw | machine learning | original thread | | ||
| 2 users recommended this thread. What they said: |
| gghyslain Sep 5, 2017 | on: Data science tips and tricks from the developer community | context |
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inlineint Jan 27, 2017 | on: Short guide to deploy Machine Learning | context
Take a look at Google's "Best Practices for ML Engineering" [1] and "Machine Learning: The High Interest Credit Card of Technical Debt" [2]. They are not tutorials, but cover a number of interesting topics related to deployment of machine learning models to production. |
I highly recommend "Best Practices for ML Engineering from Google" [1], which contains one of the best piece advice on the topic:
> "To make great products: do machine learning like the great engineer you are, not like the great machine learning expert you aren’t."
[1] Previous HN discussion: https://news.ycombinator.com/item?id=13414776