Our Books

Learn how to turn machine learning theory into solutions that work in the real world.

Imbalanced Data - Myths, Mistakes and Modern Solutions

Discover what works and what doesn’t with imbalanced data, from SMOTE to cost-sensitive learning and custom algorithms. Debunk myths, avoid common mistakes, and focus on what truly works in modern data science.

Soledad Galli

Soledad Galli

$28.99

Feature Selection in Machine Learning

Most machine learning models use too many features. The result: slower training, complex pipelines, and lack of interpretability. This book teaches you how to fix that. Working with Python open-source libraries, you'll master filter, wrapper, embedded, and advanced feature selection methods, understanding how to implement them, when each one earns its place, and exactly what to expect from it.

Soledad Galli

Soledad Galli

$29.99

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Python feature engineering cookbook

Python Feature Engineering Cookbook


70+ recipes to transform and create new features utilizing Python open-source.



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