Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

The book provides a practical approach to machine and deep learning, explaining algorithms, methodology advances, and applications in various domains. It aims to make computers solve problems like human experts by learning from data.

Format: Hardback
Length: 480 pages
Publication date: 25 February 2022
Publisher: John Wiley & Sons Inc

The book delves into the realm of machine and deep learning, offering a comprehensive and practical approach to understanding these cutting-edge technologies. Over the past two decades, machine learning and deep learning have emerged as pivotal forces in the development of software applications, revolutionizing industries such as healthcare, finance, and technology. In recent research studies, they are recognized as disruptive technologies that will shape our future lives, businesses, and the global economy. The recent surge in digital data across diverse domains, including science, engineering, the Internet of Things, biomedical research, and various business sectors, has ushered in the era of big data, requiring advanced machine learning and deep learning techniques to analyze and extract valuable insights.

Machine learning, as opposed to traditional programming, learns from data, enabling computers to solve complex problems with human-like expertise. This book aims to provide a practical guide by explaining the concepts and algorithms of machine learning and deep learning, along with their applications in various domains. It covers supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their practical implementations.

The book is organized into eighteen chapters, each dedicated to exploring different aspects of machine and deep learning. Each chapter includes algorithms and case studies, illustrating how these technologies are applied in real-world scenarios such as disease prediction, software defect prediction, online television analysis, and medical image processing. The clear and concise explanations, accompanied by detailed illustrations and examples, make the book accessible to a wide range of readers, including students, researchers, and professionals seeking to leverage the power of machine and deep learning in their respective fields.

In conclusion, this book serves as a valuable resource for anyone interested in exploring the fundamentals and methods of machine and deep learning. It provides a comprehensive and practical approach, equipping readers with the knowledge and tools necessary to implement these technologies and drive innovation in their respective industries. As the field of machine and deep learning continues to evolve and expand, this book will remain a staple reference for years to come.

Weight: 786g
Dimension: 239 x 161 x 30 (mm)
ISBN-13: 9781119821250