Glossary term
What is MAE?
In Apex Flow Academy, "MAE" means: Mean absolute error: the average size of the miss, in the same units as the label. It is taught in Machine Learning With Python: From Zero to a Working Model. Related terms include Grid search, R-squared (R2), Hyperparameter and Precision. Every Apex Flow Academy course lists the official sources it checked.
- 1 course teaches it
- plain-word definition
The facts
What is MAE?
Mean absolute error: the average size of the miss, in the same units as the label.
Where is MAE taught?
MAE is defined in Machine Learning With Python: From Zero to a Working Model.
Which lessons cover MAE?
These lessons name it in their title or objectives:
- Machine Learning With Python: From Zero to a Working Model, lesson 4.2: Measure the size of the misses
Which terms are related to MAE?
Next to MAE in the course glossaries: Grid search, R-squared (R2), Hyperparameter, Precision, Cross-validation, Recall, Pipeline and Permutation importance.
Grid searchR-squared (R2)HyperparameterPrecisionCross-validationRecallPipelinePermutation importance
The hard questions, answered straight
Bold questions people really ask. Each answer comes from the course data or a settled Academy fact.
Do I need experience before I learn MAE?
It depends on the course. Each course that teaches it lists its own prerequisites, and all are listed at beginner level:
- Machine Learning With Python: From Zero to a Working Model: Basic Python: variables, lists, dictionaries, functions, and running a .py file from a terminal.