Present book covers new paradigms in Blockchain, Big Data and Machine Learning concepts including applications and case studies. It explains dead fusion in realizing the privacy and security of blockchain based data analytic environment. Recent research of security based on big data, blockchain and machine learning has been explained through actual work by practitioners and researchers, including their technical evaluation and comparison with existing technologies. The theoretical background and experimental case studies related to real-time environment are covered as well. Aimed at Senior undergraduate students, researchers and professionals in computer science and engineering and electrical engineering, this book: Converges Blockchain, Big Data and Machine learning in one volume. Connects Blockchain technologies with the data centric applications such Big data and E-Health. Easy to understand examples on how to create your own blockchain supported by case studies of blockchain in different industries. Covers big data analytics examples using R. Includes lllustrative examples in python for blockchain creation.

Blockchain has become the cornerstone of technologies, supported by others including Big Data and Artificial Intelligence (AI). Originating from cryptocurrency, it transcends boundaries, finding resonance in finance, healthcare, e-governance, and beyond. While blockchain relies on a peer-to-peer approach, enabling nodes to collaborate without the shackles of a central authority, appropriate monitoring and updating of these technologies is a constant necessity. This is especially true for healthcare data systems, where data privacy and security concerns, especially with sensitive health information are paramount. Threads of automation in artificial intelligence (AI) weave through sectors such as business, finance, healthcare, marketing, and governance. Industrial Applications of Big Data, AI, and Blockchain delves into the pulsating realms of big data, AI, and blockchain. From natural language processing's eloquent interpretation of human language to the prowess of AI algorithms in predictive tasks, this book explores how AI enhances decision-making accuracy, catalyzing a paradigm shift in diverse industries. This book is ideal for researchers, business visionaries, tech enthusiasts, and curious minds eager to fathom the transformative potential of these technologies.

This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.

The role of deep learning for the analysis and learning of massive amounts of data from all aspects of daily-life has dramatically changed over the last few years. It is increasingly helping uncover trends leading to great successes. This book includes a collection of research manuscripts presenting state-of-the-art work in the areas of deep learning, blockchain and big data. All the manuscripts included in this book have been peer-reviewed based on aspects of novelty, originality and rigour. The main topics covered in the book include machine learning and time series, blockchain technologies and applications, data security, deep learning, and Internet of Things.

This edited book covers the challenges, opportunities, innovations, new concepts and emerging trends related to the use of machine learning, blockchain and big data analytics for IoTs. It is aimed at a broad audience of ICTs, Data science, machine learning and cybersecurity researchers.

Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Blockchain and machine learning technologies can mitigate healthcare issues such as slow access to medical data, poor system interoperability, lack of patient agency, and data quality and quantity for medical research. Blockchain technology facilitates and secures the storage of information in such a way that doctors can see a patient's entire medical history, but researchers see only statistical data instead of any personal information. Machine learning can make use of this data to notice patterns and give accurate predictions, providing more support for the patients and also in research related fields where there is a need for accurate data to predict credible results.