Framing a problem in terms of ML is a two-step process:
Verify that ML is a good approach by doing the following:
- Understand the problem.
- Identify a clear use case.
- Understand the data.
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: