Name: Understanding Models Developed with AI: Including Applications with Python and MATLAB Code
Author: Ertuğrul
ISBN: 9780443441639

Understanding Models Developed with AI: Including Applications with Python and MATLAB Code book cover

Understanding Models Developed with AI: Including Applications with Python and MATLAB Code

Author(s): Ertuğrul

Publisher: Morgan Kaufmann
Publication Date: 29 May 2026
Language: English
Print length: 320 pages
ISBN-10: 0443441634
ISBN-13: 9780443441639

Book Description

Understanding Models Developed by AI: Including Applications with Python and MATLAB Code is a comprehensive guide on the intricacies of AI models and their real-world applications. The book demystifies complex AI methodologies by providing clear explanations and practical examples that are reinforced with Python and MATLAB program codes. Its content structure emphasizes a practical, applications-driven approach to understanding AI models, with hands-on coding examples throughout each chapter. Readers will find the tools they need to build AI models, along with the knowledge to make these models accessible and interpretable to stakeholders, thus fostering trust and reliability in AI systems.

As the primary issues with the adoption of AI/ML models are reliability, transparency, interpretation of results, and bias (data and algorithm) management, this resource give researchers and developers what they need to be able to not only implement AI models, but also interpret and explain them. This is crucial in industries where decision-making processes must be transparent and understandable.

Covers the fundamental concepts needed to develop various types of Artificial Intelligence models
Includes MATLAB and Python code, allowing readers to directly implement AI models and see their applications in real-world scenarios
Each AI model is thoroughly explained, with a focus on making complex concepts accessible to both beginners and advanced users
Presents case studies from various industries, demonstrating how AI models can be effectively applied and interpreted in different contexts

Editorial Reviews

Review

Provides a comprehensive analysis of AI models and their applications, including hands-on case studies, methodologies, and coding examples

From the Back Cover

Understanding Models Developed by AI: Including Applications with Python and MATLAB Code is a comprehensive guide for readers looking to understand the intricacies of AI models and their real-world applications. This book demystifies complex AI methodologies by providing clear explanations and practical examples, reinforced with Python and MATLAB program code. It is an essential resource for readers who aim to develop and interpret AI models effectively. The primary issues with the adoption of AI/ML models are reliability, transparency, interpretation of results and bias (data and algorithm) management. Researchers and developers need to be able to not only implement AI models, but also to interpret and explain them. This is crucial in industries where decision-making processes must be transparent and understandable. This book is a valuable reference that equips readers with the tools to build AI models along with the knowledge to make these models accessible and interpretable to stakeholders, thus fostering trust and reliability in AI systems. The book’s content structure emphasizes a practical, application-driven approach to understanding AI models, with hands-on coding examples throughout each chapter.

About the Author

ÖMER FARUK ERTUĞRUL received his B.S., M.S., and Ph.D. degrees in Electrical and Electronics Engineering in 2001, 2010, and 2015, respectively. His research interests are primarily focused on machine learning and signal processing. He holds six national and one international patent. He is currently a professor and vice rector at Batman University and serves as an associate editor for NC&A, covering the Middle East, excluding Iran. Moreover, he is the co-founder at INSENSE, ABRH, INTELLIGENT, and SOFTSENSE Inc.

Dr. Tahir Çetin Akıncı completed his undergraduate studies in the Department of Electrical Engineering at Klaipeda University, Lithuania, in 2000, followed by his master’s degree in 2005 and doctorate in 2010. From 2003 to 2010, he served as a Research Assistant at Marmara University, after which he joined the Department of Electrical Engineering at Istanbul Technical University (ITU), where he earned the title of Associate Professor and, in 2020, was promoted to Professor. At ITU, Dr. Akıncı has held various administrative positions, including Deputy Director of the Institute of Science and Technology and Associate Dean of the Faculty of Electrical and Electronics Engineering. Between 2021 and 2023, Dr. Akıncı was a visiting scholar at the University of California, Riverside (UCR), where he currently serves as an Assistant Project Scientist. His research interests include artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, data analysis, and electrical energy systems.

Musa Yilmaz received his Associate Professor certificate in Electrical-Electronics and Communication Engineering. He works at the University of California, Riverside, and Batman University. He received his M.Sc. degree from Marmara University, Istanbul, Turkey, in 2004, and his Ph.D. degree from the same institution in 2013. From 2015 to 2016, Dr. Yilmaz was a visiting scholar at the Smart Grid Research Center (SMERC) at the University of California, Los Angeles (UCLA). His primary research interests include smart grid technologies, renewable energy, machine learning, and signal processing. Dr. Yilmaz is a partner of the medical company Biosys LLC. He has served as Editor-in-Chief of the Balkan Journal of Electrical and Computer Engineering (BAJECE) and the European Journal of Technique (EJT). Additionally, he is the owner of INESEG, a publishing organization. Dr. Yilmaz has authored over 50 research articles, several book chapters, and frequently delivers invited keynote lectures at international conferences. He has also led his research team as the Principal Investigator in several European projects. He is an IEEE Senior Member.

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