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Book The International Conference on Deep Learning  Big Data and Blockchain  Deep BDB 2021

Download or read book The International Conference on Deep Learning Big Data and Blockchain Deep BDB 2021 written by Irfan Awan and published by Springer Nature. This book was released on 2021-08-07 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book The International Conference on Deep Learning  Big Data and Blockchain  DBB 2022

Download or read book The International Conference on Deep Learning Big Data and Blockchain DBB 2022 written by Irfan Awan and published by Springer Nature. This book was released on 2022-08-31 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep and machine learning is the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionise industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, etc. The ground-breaking technology of blockchain also enables decentralisation, immutability, and transparency of data and applications. This event aims to enable synergy between these areas and provide a leading forum for researchers, developers, practitioners, and professionals from public sectors and industries to meet and share the latest solutions and ideas in solving cutting-edge problems in the modern information society and the economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Some of the key topics of interest include (but are not limited to): Deep/Machine learning based models Statistical models and learning Data analysis, insights and hidden pattern Data visualisation Security threat detection Data classification and clustering Blockchain security and trust Blockchain data management

Book The 4th Joint International Conference on Deep Learning  Big Data and Blockchain  DBB 2023

Download or read book The 4th Joint International Conference on Deep Learning Big Data and Blockchain DBB 2023 written by Muhammad Younas and published by Springer Nature. This book was released on 2023-10-01 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed articles which present research work on new and emerging topics such as distributed ledger technology, blockchains and architectures, smart cities, machine learning and deep learning techniques and application areas such as flight pricing, energy demand and healthcare. The intended readership of the book include researchers, developers and practitioners in the areas of deep learning, big data and blockchains technologies and their applications.

Book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Download or read book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John Macintyre and published by Springer Nature. This book was released on 2021-10-27 with total page 1169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Book Proceedings of the International Conference on Big Data  IoT  and Machine Learning

Download or read book Proceedings of the International Conference on Big Data IoT and Machine Learning written by Mohammad Shamsul Arefin and published by Springer Nature. This book was released on 2021-12-03 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a collection of high-quality peer-reviewed research papers presented at the International Conference on Big Data, IoT and Machine Learning (BIM 2021), held in Cox’s Bazar, Bangladesh, during 23–25 September 2021. The book covers research papers in the field of big data, IoT and machine learning. The book will be helpful for active researchers and practitioners in the field.

Book Big Data Analytics

    Book Details:
  • Author : Satish Narayana Srirama
  • Publisher : Springer Nature
  • Release : 2022-01-01
  • ISBN : 3030936201
  • Pages : 360 pages

Download or read book Big Data Analytics written by Satish Narayana Srirama and published by Springer Nature. This book was released on 2022-01-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th International Conference on Big Data Analytics, BDA 2021, which took place during December 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 full and 3 short papers included in this volume were carefully reviewed and selected from 41 submissions. The contributions were organized in topical sections named as follows: medical and health applications; machine/deep learning; IoTs, sensors, and networks; fundamentation; pattern mining and data analytics.

Book Big Data Analysis and Deep Learning Applications

Download or read book Big Data Analysis and Deep Learning Applications written by Thi Thi Zin and published by Springer. This book was released on 2018-06-06 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities.

Book Deep Learning  Convergence to Big Data Analytics

Download or read book Deep Learning Convergence to Big Data Analytics written by Murad Khan and published by Springer. This book was released on 2018-12-30 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning. Further, it helps students, researchers, and newcomers understand big data analytics based on deep learning approaches. It also discusses various machine learning techniques in concatenation with the deep learning paradigm to support high-end data processing, data classifications, and real-time data processing issues. The classification and presentation are kept quite simple to help the readers and students grasp the basics concepts of various deep learning paradigms and frameworks. It mainly focuses on theory rather than the mathematical background of the deep learning concepts. The book consists of 5 chapters, beginning with an introductory explanation of big data and deep learning techniques, followed by integration of big data and deep learning techniques and lastly the future directions.

Book Responsible AI

    Book Details:
  • Author : CSIRO
  • Publisher : Addison-Wesley Professional
  • Release : 2023-12-08
  • ISBN : 0138073880
  • Pages : 424 pages

Download or read book Responsible AI written by CSIRO and published by Addison-Wesley Professional. This book was released on 2023-12-08 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE FIRST PRACTICAL GUIDE FOR OPERATIONALIZING RESPONSIBLE AI ̃FROM MUL TI°LEVEL GOVERNANCE MECHANISMS TO CONCRETE DESIGN PATTERNS AND SOFTWARE ENGINEERING TECHNIQUES. AI is solving real-world challenges and transforming industries. Yet, there are serious concerns about its ability to behave and make decisions in a responsible way. Operationalizing responsible AI is about providing concrete guidelines to a wide range of decisionmakers and technologists on how to govern, design, and build responsible AI systems. These include governance mechanisms at the industry, organizational, and team level; software engineering best practices; architecture styles and design patterns; system-level techniques connecting code with data and models; and trade-offs in design decisions. Responsible AI includes a set of practices that technologists (for example, technology-conversant decision-makers, software developers, and AI practitioners) can undertake to ensure the AI systems they develop or adopt are trustworthy throughout the entire lifecycle and can be trusted by those who use them. The book offers guidelines and best practices not just for the AI part of a system, but also for the much larger software infrastructure that typically wraps around the AI. First book of its kind to cover the topic of operationalizing responsible AI from the perspective of the entire software development life cycle. Concrete and actionable guidelines throughout the lifecycle of AI systems, including governance mechanisms, process best practices, design patterns, and system engineering techniques. Authors are leading experts in the areas of responsible technology, AI engineering, and software engineering. Reduce the risks of AI adoption, accelerate AI adoption in responsible ways, and translate ethical principles into products, consultancy, and policy impact to support the AI industry. Online repository of patterns, techniques, examples, and playbooks kept up-to-date by the authors. Real world case studies to demonstrate responsible AI in practice. Chart the course to responsible AI excellence, from governance to design, with actionable insights and engineering prowess found in this defi nitive guide.

Book Proceedings of the 5th International Conference on Big Data and Internet of Things

Download or read book Proceedings of the 5th International Conference on Big Data and Internet of Things written by Mohamed Lazaar and published by Springer Nature. This book was released on 2022-07-03 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of papers in the research area of big data, cloud computing, cybersecurity, machine learning, deep learning, e-learning, Internet of Things, reinforcement learning, information system, social media and natural language processing. This book includes papers presented at the 5th International Conference on Big Data Cloud and Internet of Things, BDIoT 2021 during March 17–18, 2021, at ENSIAS, Mohammed V University in Rabat, Morocco.

Book Future Data and Security Engineering

Download or read book Future Data and Security Engineering written by Tran Khanh Dang and published by Springer Nature. This book was released on 2021-11-18 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, which was supposed to be held in Ho Chi Minh City, Vietnam, in November 2021, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers presented together with 2 invited keynotes were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: Big Data Analytics and Distributed Systems; Advances in Machine Learning for Big Data Analytics; Industry 4.0 and Smart City: Data Analytics and Security; Blockchain and IoT Applications; Machine Learning and Artificial Intelligence for Security and Privacy; Emerging Data Management Systems and Applications.

Book Big Data Analytics and Knowledge Discovery

Download or read book Big Data Analytics and Knowledge Discovery written by Matteo Golfarelli and published by Springer Nature. This book was released on 2021-09-04 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.

Book Big Data and Security

    Book Details:
  • Author : Yuan Tian
  • Publisher : Springer Nature
  • Release : 2022-03-09
  • ISBN : 9811908524
  • Pages : 761 pages

Download or read book Big Data and Security written by Yuan Tian and published by Springer Nature. This book was released on 2022-03-09 with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Big Data and Security, ICBDS 2021, held in Shenzhen, China, in November 2021 The 46 revised full papers and 13 short papers were carefully reviewed and selected out of 221 submissions. The papers included in this volume are organized according to the topical sections on cybersecurity and privacy; big data; blockchain and internet of things, and artificial intelligence/ machine learning security.

Book Big Data  Machine Learning  and Applications

Download or read book Big Data Machine Learning and Applications written by Malaya Dutta Borah and published by Springer Nature. This book was released on 2024-01-06 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Second International Conference on Big Data, Machine Learning, and Applications, BigDML 2021. The volume focuses on topics such as computing methodology; machine learning; artificial intelligence; information systems; security and privacy. This volume will benefit research scholars, academicians, and industrial people who work on data storage and machine learning.

Book Big Data Technologies and Applications

Download or read book Big Data Technologies and Applications written by Rui Hou and published by Springer Nature. This book was released on 2023-06-26 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 11th and the 12th International Conference on Big Data Technologies and Applications, BDTA 2021 and BDTA 2022, held in December 2021 and 2022. Due to COVID-19 pandemic both conferences were held virtually. The 23 full papers of BDTA 2021 and BDTA 2022 were selected from 61 submissions and present all big data technologies, such as big data collection and storage, big data management and retrieval, big data mining approaches, big data visualization, and new domains and novel applications related to these technologies.

Book Data Mining and Big Data

Download or read book Data Mining and Big Data written by Ying Tan and published by Springer Nature. This book was released on 2021-10-30 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021. The 57 full papers and 28 short papers presented in this two-volume set were carefully reviewed and selected from 258 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.

Book Proceedings of International Conference on Deep Learning  Computing and Intelligence

Download or read book Proceedings of International Conference on Deep Learning Computing and Intelligence written by Gunasekaran Manogaran and published by Springer Nature. This book was released on 2022-04-26 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at the International Conference on Deep Learning, Computing and Intelligence (ICDCI 2021), organized by Department of Information Technology, SRM Institute of Science and Technology, Chennai, India, during January 7–8, 2021. The conference is sponsored by Scheme for Promotion of Academic and Research Collaboration (SPARC) in association with University of California, UC Davis and SRM Institute of Science and Technology. The book presents original research in the field of deep learning algorithms and medical imaging systems, focusing to address issues and developments in recent approaches, algorithms, mechanisms, and developments in medical imaging.