Thread by @chipro

To learn how to design machine learning systems, I find it really helpful to read case studies to see how great teams deal with different deployment requirements and constraints. Here are some of my favorite case studies.

Topics covered: lifetime value, ML project workflow, feature engineering, model selection, prototyping, moving prototypes to production. It's completed with lessons learned and looking ahead!

medium.com/airbnb-enginee…

Netflix streams to over 117M members worldwide, half of those living outside the US. The company uses machine learning to predict the network quality, detect device anomaly, handle predictive caching.
medium.com/netflix-techbl…

This article explores the tradeoff between complexity and interpretability, performance and ease for production, for the classic task of fraud detection. (4/n)
eng.lyft.com/from-shallow-t…

Instacart uses machine learning to solve the task of path optimization. The article explains the entire process of system design, from framing the problem, collecting data, algorithm & metric selection, with visualization thrown in. (5/n)
tech.instacart.com/space-time-and…

Fashion Taste API attempted to qualify people's fashion taste using machine learning! (6/n) medium.com/hackernoon/how…

This article walks you step by step through a canonical example of the ranking and recommendation problem.

Four main steps: system design, personalization, online scoring, and business aspect (7/n)

medium.com/airbnb-enginee…