Framing a problem in terms of ML is a two-step process:

  1. Verify that ML is a good approach by doing the following:

    • Understand the problem.
    • Identify a clear use case.
    • Understand the data.
  2. Frame the problem in ML terms by doing the following:

    • Define the ideal outcome and the model's goal.
    • Identify the model's output.
    • Define success metrics.

These steps can save time and resources by setting clear goals and providing a shared framework for working with other ML practitioners.

Use the following exercises to frame an ML problem and formulate a solution:

Privacy and ethics

Using ML can bring up privacy and ethical concerns. Before productionalizing a model, review the following resources:

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