Glossary term
What is Cross-validation?
In Apex Flow Academy, "Cross-validation" means: Cutting the training rows into folds and using each fold as the exam once, then averaging the scores. It is taught in Machine Learning With Python: From Zero to a Working Model. Related terms include Pipeline, Hyperparameter, Underfitting and Grid search. Every Apex Flow Academy course lists the official sources it checked.
- 1 course teaches it
- plain-word definition
The facts
What is Cross-validation?
Cutting the training rows into folds and using each fold as the exam once, then averaging the scores.
Where is Cross-validation taught?
Cross-validation is defined in Machine Learning With Python: From Zero to a Working Model.
Which lessons cover Cross-validation?
These lessons name it in their title or objectives:
- Machine Learning With Python: From Zero to a Working Model, lesson 5.2: Cross-validation: five exams instead of one
- Machine Learning With Python: From Zero to a Working Model, lesson 5.4: Tune settings without peeking
Which terms are related to Cross-validation?
Next to Cross-validation in the course glossaries: Pipeline, Hyperparameter, Underfitting, Grid search, Overfitting, MAE, Standardising (scaling) and R-squared (R2).
PipelineHyperparameterUnderfittingGrid searchOverfittingMAEStandardising (scaling)R-squared (R2)
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 Cross-validation?
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.