Feature engineering is the art and science of creating features from data that can help machine learning algorithms learn better and faster. Features are the attributes or variables that describe ...

Feature engineering involves systematically transforming raw data into meaningful and informative features (predictors). It is an indispensable process in machine learning and data science.

Feature engineering creates features from the existing raw data in order to increment the predictive power of the machine learning algorithms. Generally, the feature engineering process is applied to ...

Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient.

What is this book about? Feature engineering is invaluable for developing and enriching your machine learning models. In this book, you will work with the best Python tools to streamline your feature ...

Persistence diagrams are an increasingly useful shape descriptor from Topological Data Analysis. One of their more popular uses to date has been as features for machine learning tasks, with success in ...

This book chapter explores feature engineering techniques in machine learning, covering topics such as rescaling, handling categorical data, time‐related feature engineering, missing value handling, ...