Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists

The Feature Engineering Book is a comprehensive guide to extracting and transforming features for machine learning models.

With practical exercises throughout, this book covers techniques for numeric data, natural text, frequency-based filtering, encoding categorical variables, model-based feature engineering, and image feature extraction.

The author's experience in the field provides valuable insights into real-world applications of feature engineering.

This book is a must-read for anyone looking to improve their machine learning models through effective feature engineering.