How do you design and run rigorous machine learning experiments? What practices ensure your conclusions are valid and reproducible?

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Rigorous experimentation is the foundation of trustworthy machine learning research and development. Without disciplined methodology, it is easy to draw false conclusions from noise, overfit to validation sets, or produce results that others cannot reproduce.