AI engineering glossary · ML fundamentals
What is problem framing?
Problem framing (also called ML problem framing): Turning a business need into a well-defined machine learning task: deciding what to predict, what data exists, how success is measured and what action follows. Good framing avoids building an accurate model for the wrong question.
Problem framing: an example
Reducing customer churn is framed as predicting which customers will leave in the next 30 days so that retention offers can be targeted.
Related terms
More ML fundamentals terms
- Random search
- Random seed
- Regression
- Regularisation
- Representation learning
- Reproducibility
- Selection bias
- Self-supervised learning
Where you learn it
Problem framing is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.