Feature Engineering

Intermediate

Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.

Full Definition

Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.

Keywords

transformations signals

Domains

Foundations & Theory

Related Terms

Latent Space related to

The internal space where learned representations live; operations here often correlate with semantics or generative f...

 Model related to

A parameterized mapping from inputs to outputs; includes architecture + learned parameters.

 Parameters related to

The learned numeric values of a model adjusted during training to minimize a loss function.

 Loss Function related to

A function measuring prediction error (and sometimes calibration), guiding gradient-based optimization.

 Artificial Intelligence related to

The field of building systems that perform tasks associated with human intelligence—perception, reasoning, language, ...

 Concept Drift related to

The relationship between inputs and outputs changes over time, requiring monitoring and model updates.

 Feature related to

A measurable property or attribute used as model input (raw or engineered), such as age, pixel intensity, or token ID.

Concept Map

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