Defining Scope & Creating Baselines

Managing your machine learning experiments can be a painful and tedious process. But the good news is that it doesn’t have to be. Managing experiments can be straightforward and simple. This introductory course will help you understand the key concepts of experiment management and how to implement it at your organization.

In part one of this series, you’ll learn the critical steps required to successfully manage your experiments in an automated fashion, at scale. This includes:

  • Key principles of machine learning experiment management
  • How to define and document the scope and success criteria for your project
  • Approaches to setting up dumb baselines that take production and real-world variables into account

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Standardizing the Experiment