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ML system design: 300 case studies to learn from

A database of 300 case studies from 80+ companies.
How do companies like Netflix, Airbnb, and Doordash apply machine learning to improve their products and processes? We put together a database of 300 case studies from 80+ companies that share practical ML use cases and learnings from designing ML systems.

Real-world ML systems

All the content belongs to respective parties. We simply put the links together

Selection criteria. Here is how we selected the case studies to include: 

  • It is a blog, paper, or article about a machine learning system created in-house (not by a vendor that sells or implements ML solutions for others).
  • It has sufficient detail on the ML use case and implementation: who the model is for, the ML model design, evaluation criteria, deployment architecture, etc. The more, the better. 
  • It covers a real-world ML system that is used in production.
  • It describes one particular ML use case. There are only a few exceptions that detail multiple ML projects at once — about causal ML or generative AI, for example.

Did we miss some great ML case studies? Let us know! Our Discord Community with 2000+ ML practitioners is the best place to share feedback.

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