Artificial Intelligence

Foundations, Ethics, and Real-World Applications
1. Auflage 2026
ISBN: 978-1-041-34307-3
Verlag: Taylor & Francis Ltd

Buch, Englisch, 360 Seiten, Format (B × H): 156 mm x 234 mm

The book emphasizes the importance of responsible artificial intelligence practices, including transparency, bias mitigation, and ethical decision-making. Each chapter combines theoretical depth with practical implementation through Python coding exercises, real-world examples, and deployment strategies.

This book:

- Covers the full breadth of artificial intelligence topics, from foundational concepts like data preprocessing and supervised learning to advanced topics in deep learning, reinforcement learning, and natural language processing.

- Incorporates hands-on Python coding exercises to build practical skills and includes optimization techniques, model deployment strategies, and ethical artificial intelligence practices.

- Provides in-depth coverage of explainable and ethical artificial intelligence, emphasizing the importance of developing systems that align with societal values and norms.

- Addresses critical issues such as fairness, transparency, accountability, and bias mitigation.

- Presents case studies and examples from industries like healthcare, finance, and robotics.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communication engineering, artificial intelligence, machine learning, computer science and engineering, and information technology.

Zielgruppe

Academic, Postgraduate, and Undergraduate Advanced

Autoren/Hrsg.

Acharya, Deepak Bhaskar

Naik, Swapnali

Pandey, Bishwajeet Kumar

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision

Inhaltsverzeichnis

1. Introduction to AI. 2. Data Preparation and Preprocessing. 3. Supervised Learning. 4. Unsupervised Learning. 5. Neural Networks and Deep Learning. 6. Advanced Deep Learning Architectures. 7. Reinforcement Learning. 8. Advanced Reinforcement Learning: Algorithms and Systems. 9. Natural Language Processing (NLP). 10. Explainable and Ethical AI. 11. Optimization and Hyperparameter Tuning. 12. Real-World AI Applications Across Industries. 13. Deploying AI Models: Architectures, Optimization, and MLOps Practices. 14. Deploying EEG-to-Text AI Systems: A Scalable Architecture Featuring the NeuroClean Pipeline. 15. Future Trends in AI.

Über Autor(innen)

Swapnali Naik is Scientist ‘D’ and Joint Director (Technical) at National Institute of Electronics and Information Technology, New Delhi, under the Ministry of Electronics and Information Technology (MeitY), Government of India, and currently heads the NIELIT East Delhi office. She holds a postgraduate degree in Computer Science and Engineering and has over 20 years of professional experience across premier government organizations under IT Ministry IECT domain. Her areas of expertise include Artificial Intelligence, Machine Learning, Data Analytics, software development, training, mentoring, and execution of large-scale government-funded capacity-building initiatives. She is the author of the book Think AI and has contributed to research and development through several technical publications. She is currently pursuing Ph.D. research in the field of Artificial Intelligence. At NIELIT, Ms. Naik has been actively involved in strengthening digital skilling initiatives, promoting emerging technologies, and enhancing institutional readiness through various national-level programs. As Chief Investigator for the Future Skills Prime Programme (AI Technology), she is leading initiatives focused on developing an AI-skilled workforce and advancing capacity building in emerging technologies across the country. She has also served as a resource person in several national and international seminars, workshops, and training programs related to AI and digital technologies. Her professional interests include AI-driven education and skilling, emerging technologies, digital transformation, and capacity building for a future-ready workforce.

Deepak Acharya is a Principal Research Scientist in Artificial Intelligence with expertise in machine learning, generative AI, remote sensing, and applied AI systems. His work focuses on developing intelligent, data-driven solutions for real-world challenges across environmental, scientific, and enterprise domains. He has contributed to academic and interdisciplinary AI initiatives and has professional interests in trustworthy AI, environmental intelligence, and practical AI deployment.

Bishwajeet Pandey is a Professor at GL Bajaj Institute of Technology and Management, Greater Noida, India, and a Visiting Professor at UCSI University, Malaysia (QS World Rank 265). He has been a Senior Member of IEEE since 2019. Dr. Pandey holds an MTech in Computer Science from IIIT Gwalior, India, and a PhD in Computer Science from the Gran Sasso Science Institute, Italy. He has previously taught at several esteemed institutions, including Chitkara University (Chandigarh), Jain University (Bangalore), Astana IT University (Kazakhstan), Eurasian National University (Kazakhstan — QS World Rank 321), and Walsh College (USA). A prolific researcher, Dr. Pandey has authored over 30 books and published more than 250+ Scopus-indexed research papers, accumulating over 5000+ citations. His leadership experience includes serving as the Research Head of the School of CSE at Jain University, Bangalore (2021–2023) and heading the International Global Academic Partnership Committee at the Birla Institute of Applied Science, Bhimtal (2020–2021). In 2023, he was honoured with the prestigious Professor of the Year Award at Lord’s Cricket Ground by the London Organisation of Skills Development. Dr. Pandey’s greatest strength lies in his extensive global academic network. He has visited 51 countries, participated in 105 international conferences, and co-authored papers with 218 professors from 93 universities across 42 nations. He also serves as the Chair of two IEEE International Conferences—ICAIC (AI in Cybersecurity) and GAISS (Generative AI for Secure Systems) —held in Houston and Austin, USA.