4 docs tagged with "data-science"

Reducing feature complexity while preserving information: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

Techniques for identifying and keeping only the most relevant features using filter, wrapper, and embedded methods.

A comprehensive guide to creating, transforming, and selecting features to maximize Machine Learning model performance.

A comprehensive introduction to the Machine Learning Tutorial structure, purpose, and key learning outcomes for CodeHarborHub learners.