Four short links: 9 October 2019
Data Playbook, Global Politics Meets Tech, ML Models, and Lock-free Programming
- IFRC Data Playbook Toolkit — The Data Playbook Beta is a recipe book or exercise book with examples, best practices, how-to’s, session plans, training materials, matrices, scenarios, and resources. The data playbook will provide resources for National Societies to develop their literacy around data, including responsible data use and data protection. The content aims to be visual, remixable, collaborative, useful, and informative.
- The China Cultural Clash — as more companies have a financial interest in China (either partially owned by, or hoping to sell hard into), employees and users are being discouraged from sharing opinions that China disagrees with.
- 150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com (Adrian Colyer) — Oddly enough given the paper title, the six lessons are never explicitly listed or enumerated in the body of the paper, but they can be inferred from the division into sections. My interpretation of them is as follows: (1) Projects introducing machine learned models deliver strong business value; (2) Model performance is not the same as business performance; (3) Be clear about the problem you’re trying to solve; (4) Prediction serving latency matters; (5) Get early feedback on model quality; (6) Test the business impact of your models using randomized controlled trials (follows from #2).
- Awesome Lock-Free — A collection of resources on wait-free and lock-free programming.
