sota-ml-engineering

State-of-the-art ML engineering / MLOps rules (2026) for BUILDING and AUDITING production machine-learning systems — the training→serving→monitoring lifecycle of classical/predictive ML. Distinct from LLM apps (prompts/RAG/agents → sota-llm-engineering). Covers ML system architecture (feature stores, model registry, reproducibility), data & features (leakage, train/serve skew, versioning), training & experiment…