The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods.
The text discusses theoretical background of algorithms and applications of methods using social science problems. It explores... Læs mere
This book explores RSSI-based localization, device-free detection, and machine learning integration, providing practical insights into wireless sensing applications for navigation, security, healthcare, and intelligent IoT systems.
This book explores RSSI-based localization, device-free detection, and machine learning integration, providing practical insights into wireless sensing applications for navigation, security, healthcare, and intelligent IoT systems.
Traditionally, classical multivariate statistical methods have been applied to relate cultural materials recovered at archaeological sites to their... Læs mere
Traditionally, classical multivariate statistical methods have been applied to relate cultural materials recovered at archaeological sites to their... Læs mere
This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing.
This collection of chapters from specialists presents principles and practices of machine learning, along with a number of example areas of site... Læs mere
The book provides mathematicians an overview of AI and machine learning relevant to operations research. It focuses decision modeling and optimization models as well as algorithms.
This book explores how advanced machine learning techniques are transforming healthcare, highlighting innovative applications in... Læs mere