Computational Statistical Methodologies and Modeling for Artificial Intelligence

This book provides a comprehensive coverage of computational statistics-based approaches for Artificial Intelligence, covering fundamentals through applications in various AI systems. It is designed for researchers, academics, postgraduate students, and specialists in data science, mathematical modeling, and AI, and will also be a valuable resource for electrical, computer, and optical engineering professionals.

Format: Hardback
Length: 360 pages
Publication date: 31 March 2023
Publisher: Taylor & Francis Ltd

This comprehensive book delves into the realm of computational statistics, offering a comprehensive exploration of its applications in the field of Artificial Intelligence. With its primary objective of providing a thorough understanding of the fundamentals through the application of diverse mathematical modelling and statistical techniques, this text aims to serve as a valuable resource for researchers, academics, postgraduate students, and specialists in data science, mathematical modelling, and Artificial Intelligence. Furthermore, it will also prove to be an indispensable tool for professionals in electrical, computer, and optical engineering.

The book's key features include:

Comprehensive Coverage: This book offers a comprehensive treatment of computational statistics, encompassing both theoretical foundations and practical applications. It provides a thorough exploration of the various mathematical modelling and statistical techniques employed in Artificial Intelligence systems, enabling readers to gain a deep understanding of the field.

Real-World Problem Applications: The book showcases a wide range of real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence. By presenting case studies and practical examples, readers can gain insights into how these techniques are applied in practical scenarios and how they contribute to the development of intelligent systems.

Evolution of Fundamental Research: The book examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications. It sheds light on the processes involved in translating scientific discoveries into practical applications, highlighting the importance of collaboration and interdisciplinary research in the field of Artificial Intelligence.

Applications Involving Analytical and Statistical Solutions: The book delves into the applications involving analytical and statistical solutions, providing foundational and advanced concepts for beginners and industry professionals alike. It covers a wide range of topics, including data analysis, pattern recognition, machine learning, and optimization, offering practical insights and techniques for applying these methods in various AI systems.

Dynamic Perspective: The book provides a dynamic perspective to the concept of computational statistics for the analysis of data and applications in intelligent systems. With an emphasis on ensuring sustainability issues for ease of different stakeholders in various fields, it explores the role of computational statistics in addressing complex problems and driving innovation in the field of Artificial Intelligence.

Integration of Recent Methodologies and Challenges: The book integrates recent methodologies and challenges by employing mathematical modelling and statistical techniques for Artificial Intelligence. It discusses the latest advancements in the field, such as deep learning, big data analysis, and natural language processing, and how these techniques are being leveraged to enhance the capabilities and performance of AI systems.

In conclusion, this comprehensive book offers a valuable resource for anyone interested in computational statistics and its applications in the field of Artificial Intelligence. It provides a thorough understanding of the fundamentals through the application of diverse mathematical modelling and statistical techniques, enabling readers to contribute to the development of intelligent systems and drive innovation in their respective fields.

Weight: 688g
Dimension: 240 x 164 x 26 (mm)
ISBN-13: 9781032170800