Blog Post··4 min read
ML System Design: A Framework That Actually Works
The universal seven-step framework for any ML system design problem — and the specific mistakes that make interviewers fail strong candidates.
The universal seven-step framework for any ML system design problem — and the specific mistakes that make interviewers fail strong candidates.
Feature stores (online/offline duality), data vs model parallelism for distributed training, and why A/B testing ML models is harder than product A/B tests.