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Data collection is an imperfect science, and incredibly complex machine learning (ML) systems often lack specification – so in order to achieve reproducibility, experimentation is necessary, and must be standardized.

The reproducibility crisis in ML is a serious barrier to future progress for any organization. Read this e-book to:

• Learn the 7 steps in standardizing experimentation
• Identify the benefits and steps in achieving reproducibility
• Understand why the CACE principle matters
• And more