Glossary term
What is Overfitting?
In Apex Flow Academy, "Overfitting" means: Learning the quirks of the training rows so well that the model does worse on new rows. It is taught in Machine Learning With Python: From Zero to a Working Model. Related terms include Standardising (scaling), Underfitting, One-hot encoding and Pipeline. Every Apex Flow Academy course lists the official sources it checked.
- 1 course teaches it
- plain-word definition
The facts
What is Overfitting?
Learning the quirks of the training rows so well that the model does worse on new rows.
Where is Overfitting taught?
Overfitting is defined in Machine Learning With Python: From Zero to a Working Model.
Which lessons cover Overfitting?
These lessons name it in their title or objectives:
- Machine Learning With Python: From Zero to a Working Model, lesson 4.4: Underfitting, overfitting and the validation set
Which terms are related to Overfitting?
Next to Overfitting in the course glossaries: Standardising (scaling), Underfitting, One-hot encoding, Pipeline, Median, Cross-validation, Impute and Hyperparameter.
Standardising (scaling)UnderfittingOne-hot encodingPipelineMedianCross-validationImputeHyperparameter
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 Overfitting?
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.