Gaurav – författare

Behavioral finance challenges the traditional assumption that individuals are rational by focusing on the cognitive and emotional aspects of finance, which draws on psychology, sociology, and biology to investigate true financial behavior. The financial sector requires sound understanding of market dynamics and strategic issues to meet future challenges in the field. Behavioral Finance and Decision-Making Models seeks to examine behavioral biases and their impact on investment decisions in order to develop better future plans and strategies in the financial sector. While highlighting topics including behavioral approach, financial regulation, and globalized sector, this book is intended for policymakers, technology developers, managers, government officials, academicians, researchers, and advanced-level students.

Behavioral finance challenges the traditional assumption that individuals are rational by focusing on the cognitive and emotional aspects of finance, which draws on psychology, sociology, and biology to investigate true financial behavior. The financial sector requires sound understanding of market dynamics and strategic issues to meet future challenges in the field. Behavioral Finance and Decision-Making Models seeks to examine behavioral biases and their impact on investment decisions in order to develop better future plans and strategies in the financial sector. While highlighting topics including behavioral approach, financial regulation, and globalized sector, this book is intended for policymakers, technology developers, managers, government officials, academicians, researchers, and advanced-level students.

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.