Glossary term
What is One-hot encoding?
In Apex Flow Academy, "One-hot encoding" means: Turning a text column into one 0-or-1 column for each category. It is taught in Machine Learning With Python: From Zero to a Working Model. Related terms include Median, Standardising (scaling), Impute and Overfitting. Every Apex Flow Academy course lists the official sources it checked.
- 1 course teaches it
- plain-word definition
The facts
What is One-hot encoding?
Turning a text column into one 0-or-1 column for each category.
Where is One-hot encoding taught?
One-hot encoding is defined in Machine Learning With Python: From Zero to a Working Model.
Which terms are related to One-hot encoding?
Next to One-hot encoding in the course glossaries: Median, Standardising (scaling), Impute, Overfitting, Data leakage, Underfitting, Validation set and Pipeline.
MedianStandardising (scaling)ImputeOverfittingData leakageUnderfittingValidation setPipeline
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 One-hot encoding?
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.