6. How model improvement practices evolved
Trace how model refinement moved from statistical validation and hand-built features to machine learning competitions, deep learning, MLOps, data-centric AI, and foundation models. This history explains why today’s practitioners care so much about reproducible experiments, high-quality data, and post-training refinement.