Results for "features"
Feature Engineering
Intermediate
Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.
Representation Learning
Intermediate
Automatically learning useful internal features (latent variables) that capture salient structure for downstream tasks.
Model Inversion
Intermediate
Inferring sensitive features of training data.
Feature Store
Intermediate
Centralized repository for curated features.