Machine LearningLesson 13Free preview
ML Terminology
This lesson is part of A.I. · All levels
Summary
Understanding the basic terms of machine learning makes it easy for us to read documents and model code. Key terms include features (input characteristics), labels (predicted responses), models (representations of patterns studied), as well as numerical and categorical data. These terms are used consistently in almost all ML libraries.
Key points
- Features are input values in the form of data characteristics.
- Labels are predictable output.
- Numerical data is numerical; categorical data is categorical, such as color or type.
- Models are representations of patterns of training outcomes that are ready to be used to predict.
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