Hands-On Ensemble Learning with Python

Preface

Ensembling is a technique for combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior predictive power. This book will demonstrate how you can use a variety of weak algorithms to make a strong predictive model. With its hands-on approach, you'll not only get up to speed on the basic theory, but also the application of various ensemble learning techniques. Using examples and real-world datasets, you'll be able to produce better machine learning models to solve supervised learning problems such as classification and regression. Later in the book, you'll go on to leverage ensemble learning techniques such as clustering to produce unsupervised machine learning models. As you progress, ...