Ebook: Imbalanced Classification with Python: Better Metrics, Balance Skewed Classes, Cost-Sensitive Learning

Imbalanced classification are those classification tasks where the distribution of examples across the classes is not equal.

Cut through the equations, Greek letters, and confusion, and discover the specialized techniques data preparation techniques, learning algorithms, and performance metrics that you need to know.

Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently develop robust models for your own imbalanced classification projects.