Explainable Artificial Intelligence: A Practical Guide
River Publishers (Verlag)
978-87-7004-713-5 (ISBN)
This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI.
Technical topics discussed in the book include:
Explainable AI overview
Understanding black box models
Techniques for model interpretability
Practical applications of XAI
Future trends and challenges in XAI
Dr. Parikshit Narendra Mahalle is a senior member IEEE and is Professor, Dean Research and Development and Head of Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, India. He completed his Ph.D. from Aalborg University, Denmark and continued as Post Doc Researcher at CMI, Copenhagen, Denmark. He has 23+ years of teaching and research experience. He is an ex-member of the Board of Studies in Computer Engineering, ex-Chairman Information Technology, SPPU and various Universities and autonomous colleges across India. He has 12 patents and has 200+ research publications. Mr. Yashwant Sudhakar Ingle is presently working at VIIT, Pune as Assistant Professor in Department of AI&DS. He has a total of 15 years work experience. He is pursuing a Ph.D. from SPPU and completed his M.Tech. CSE from Visvesvaraya National Institute of Technology, Nagpur and his B.E. CSE from Amravati University. Mr. Ingle has 4 design patents granted, 1 US patent published, 25 Indian utility patents published, 4 software copyrights and 2 literary research copyrights registered. He has authored a Springer book recently on Data Centric AI: A Beginner’s Guide. He has published 25+ papers in Scopus, Web of Science journals, IEEE and Springer International Conferences and received 4 Best Paper Awards at the RACE National Conference 2021.
Preface 1. Explainable Artificial Intellience Overview 2. Understanding Black Box Models 3. Techniques for Model Interpretability 4. Practical Applications of XAI 5. Future Trends and Challenges in XAI Author biography Index
| Erscheinungsdatum | 22.11.2024 |
|---|---|
| Reihe/Serie | River Publishers Rapids Series on Intelligence in Chips |
| Zusatzinfo | 14 Illustrations, color; 1 Illustrations, black and white |
| Verlagsort | Gistrup |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 200 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Umwelttechnik / Biotechnologie | |
| ISBN-10 | 87-7004-713-8 / 8770047138 |
| ISBN-13 | 978-87-7004-713-5 / 9788770047135 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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