Books in Machine learning

IoT Security

1st Edition
October 1, 2025
SK Hafizul Islam + 3 more
English

IoT Security: Fundamentals and Key Enabling Technologies explores the complex interactions between Internet of Things (IoT) and the pressing need for effective cybersecurity solutions. Diving into real-world case studies to provide insights into implementing efficient security measures that safeguard against online dangers, this book comprehensively analyzes the challenges and possibilities presented by intelligent technologies fueling transformational change, emphasizing the crucial role cybersecurity plays in defending networks, data, and user privacy in an increasingly interconnected digital ecosystem. Coverage includes cryptographic methods, communication networks, device identity and access, data governance and privacy, as well as regulatory frameworks and standards for IoT security. Computer science researchers and engineers will benefit from this compilation of cutting edge research and practical case studies, learning how to minimize risks for IoT and intelligent technologies.

Quantum Computational AI

1st Edition
August 5, 2025
Long Cheng + 2 more
English
Paperback
9 7 8 0 4 4 3 3 0 2 5 9 6
eBook
9 7 8 0 4 4 3 3 0 2 6 0 2

Quantum Computational AI: Algorithms, Systems, and Applications represents an emerging, fast evolving field. The rapid advancements in both quantum computing and AI necessitate a new resource that encapsulates the latest theories, algorithms, and practical applications at the intersection of these domains. Quantum Computational AI: Algorithms, Systems and Applications dives into the intersection of quantum computing and artificial intelligence, showcasing how they can come together to form powerful new computational frameworks. Through the lens of expert contributors, this book navigates through quantum algorithms, explores the design of quantum systems, and demonstrates real-world applications across various sectors. Designed to be both informative and accessible, this book is perfect for academics, researchers, industry professionals, and students keen to be on the forefront of quantum and AI technologies. With a blend of theory and practical examples, the book provides a solid understanding of how quantum principles can be leveraged to advance AI, opening doors to unprecedented possibilities. This book provides a consolidated, comprehensive, and accessible resource, which elucidates the synergy between quantum algorithms and AI systems, showcasing how they can be harmoniously integrated to unlock new computational paradigms and solve complex real-world problems.

Edge Intelligence in Cyber-Physical Systems

1st Edition
August 1, 2025
Wei Yu
English
Paperback
9 7 8 0 4 4 3 2 6 5 7 2 3
eBook
9 7 8 0 4 4 3 2 6 5 7 3 0

Edge Intelligence in Cyber-Physical Systems: Foundations and Applications provides a comprehensive overview of best practices for building edge intelligence into cyber-physical systems. This book covers the foundations and applications of synergizing machine learning at the edge of CPS, leveraging an edge computing infrastructure. Divided into four parts, the first section of the book reviews the foundations, principles, and representative application domains of CPS. The second part covers machine learning, edge computing, and their needs in CPS, defining edge intelligence and its principles, challenges, and research directions. The third part presents tutorials and foundational research works on realizing edge intelligence in representative CPS. The fourth part explores the problem space of threats and countermeasures in building edge intelligence into CPS. Researchers, graduate students and professionals in computer science, data science, and electrical engineering will find this to be a valuable resource on the principles and applications of edge intelligence in cyber-physical systems as well as the development of interdisciplinary techniques to advance the field.

Deep Learning Assessment of Neurological Imaging

1st Edition
July 1, 2025
Tripti Goel + 3 more
English

"Deep Learning Assessment of Neurological Imaging" provides an introduction to deep learning structures and pre-processing methods for detecting MRI anomalies. It also provides a comprehensive account of deep learning research on MRI images for Alzheimer's disease, Parkinson's disease, and schizophrenia, and a discussion on current research issues and future objectives. The book is a valuable resource to guide new entrants in the field to make a meaningful impact in their development efforts. The book concludes with a brief overview of the problems discussed and potential future advancements in the field.

Advanced Machine Learning for Cyber-Attack Detection in IoT Networks

1st Edition
June 1, 2025
Dinh Thai Hoang + 3 more
English
Paperback
9 7 8 0 4 4 3 2 9 0 3 2 9
eBook
9 7 8 0 4 4 3 2 9 0 3 3 6

Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems. Chapters investigate the key challenges and vulnerabilities found in IoT security, how to handle challenges in data collection and pre-processing specific to IoT environments, as well as what metrics to consider for evaluating the performance of machine learning models. Other sections look at the training, validation, and evaluation of supervised learning models and present case studies and examples that demonstrate the application of supervised learning in IoT security.

Deep Learning in Action: Image and Video Processing for Practical Use

1st Edition
March 12, 2025
Abdussalam Elhanashi + 1 more
English
eBook
9 7 8 0 4 4 3 3 0 0 7 9 0

Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.

Artificial Neural Networks and Type-2 Fuzzy Set

1st Edition
February 19, 2025
Snehashish Chakraverty + 2 more
English
eBook
9 7 8 0 4 4 3 3 2 8 9 5 4

Soft computing is an emerging discipline which aims to exploit tolerance for imprecision, approximate reasoning, and uncertainty to achieve robustness, tractability, and cost effectiveness for building intelligent machines. Soft computing methodologies include neural networks, fuzzy sets, genetic algorithms, Bayesian networks, and rough sets, among others. In this regard, neural networks are widely used for modeling dynamic solvers, classification of data, and prediction of solutions, whereas fuzzy sets provide a natural framework for dealing with uncertainty. Artificial Neural Networks and Type-2 Fuzzy Set: Elements of Soft Computing and Its Applications covers the fundamental concepts and the latest research on variants of Artificial Neural Networks (ANN), including scientific machine learning and Type-2 Fuzzy Set (T2FS). In addition, the book also covers different applications for solving real-world problems along with various examples and case studies. It may be noted that quite a bit of research has been done on ANN and Fuzzy Set theory/ Fuzzy logic. However, Artificial Neural Networks and Type-2 Fuzzy Set is the first book to cover the use of ANN and fuzzy set theory with regards to Type-2 Fuzzy Set in static and dynamic problems in one place. Artificial Neural Networks and Type-2 Fuzzy Sets are two of the most widely used computational intelligence techniques for solving complex problems in various domains. Both ANN and T2FS have unique characteristics that make them suitable for different types of problems. This book provides the reader with in-depth understanding of how to apply these computational intelligence techniques in various fields of science and engineering in general and static and dynamic problems in particular. Further, for validation purposes of the ANN and fuzzy models, the obtained solutions of each model in the book is compared with already existing solutions that have been obtained with numerical or analytical methods.

Data Mining

5th Edition
February 4, 2025
Ian H. Witten + 4 more
English
Paperback
9 7 8 0 4 4 3 1 5 8 8 8 9
eBook
9 7 8 0 4 4 3 1 5 8 8 9 6

Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today’s techniques coupled with the methods at the leading edge of contemporary research

Dimensionality Reduction in Machine Learning

1st Edition
February 4, 2025
Jamal Amani Rad + 2 more
English
Paperback
9 7 8 0 4 4 3 3 2 8 1 8 3
eBook
9 7 8 0 4 4 3 3 2 8 1 9 0

Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data.

Quantum Computing for Healthcare Data

1st Edition
January 17, 2025
Nagasubramanian Gayathri + 2 more
English
Paperback
9 7 8 0 4 4 3 2 9 2 9 7 2
eBook
9 7 8 0 4 4 3 2 9 2 9 8 9

Quantum Computing for Healthcare Data: Revolutionizing the Future of Medicine presents an advanced overview of the fundamentals of quantum computing, from the transition of traditional to quantum computing, to the challenges and opportunities encountered as various industries enter into the paradigm shift. The book investigates how quantum AI, quantum data processing, and quantum data analysis can best be integrated into healthcare data systems. The book also introduces a range of case studies which feature applications of quantum computing in connected medical devices, medical simulations, robotics, medical diagnosis, and drug discovery. The book will be a valuable resource for researchers, graduate students, and professional programmers and computer engineers working in the areas of healthcare data management and analytics, blockchain, IoT, and big data analytics.

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