Ensemble Methods For Machine Learning

Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content.

Learn supervised and unsupervised learning, data preprocessing, and model building. Work on real-world projects.

Learn supervised and unsupervised learning, data preprocessing, and model building. Work on real-world projects.

This book highlights artificial intelligence algorithms used in implementation of automated pricing. It presents the process for building automated pricing models from crawl data, preprocessed data to implement models, and their applications. The book also focuses on machine learning and deep learning methods for pricing, including from regression methods to hybrid and ensemble methods. The computational experiments are presented to illustrate the pricing processes and models.

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

Master the MLA-C01 AWS Machine Learning Engineer Exam: SageMaker, Bedrock, and AI Skills for Certification Success!

Master the MLA-C01 AWS Machine Learning Engineer Exam: SageMaker, Bedrock, and AI Skills for Certification Success!