How to: MLOps: People & Processes
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1. [Scaling An ML Team (0–10 People)](https://medium.com/aquarium-learning/scaling-an-ml-team-0-10-people-ae024f3a89f3)
1. [The Knowledge Repo project is focused on facilitating the sharing of knowledge between data scientists and other technical roles.](https://github.com/airbnb/knowledge-repo) 
1. [Scaling Knowledge at Airbnb](https://medium.com/airbnb-engineering/scaling-knowledge-at-airbnb-875d73eff091)
1. [Models for integrating data science teams within companies A comparative analysis](https://djpardis.medium.com/models-for-integrating-data-science-teams-within-organizations-7c5afa032ebd)
1. [How to Write Better with The Why, What, How Framework. How to write design documents for data science/machine learning projects? (by Eugene Yan)](https://eugeneyan.com/writing/writing-docs-why-what-how/)
1. [Technical Writing Courses](https://developers.google.com/tech-writing)
1. [Building a data team at a mid-stage startup: a short story. By Erik Bernhardsson](https://erikbern.com/2021/07/07/the-data-team-a-short-story.html)
1. [The Cultural Benefits of Artificial Intelligence in the Enterprise. by Sam Ransbotham, François Candelon, David Kiron, Burt LaFountain, and Shervin Khodabandeh](https://web-assets.bcg.com/2a/d0/ebfb860a4e05aa9e4729b083da4b/the-cultural-benefits-of-artificial-intelligence-in-the-enterprise.pdf)