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Deep Learning Innovations And Their Convergence With Big Data
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Book Synopsis Deep Learning Innovations and Their Convergence With Big Data by : Karthik, S.
Download or read book Deep Learning Innovations and Their Convergence With Big Data written by Karthik, S. and published by IGI Global. This book was released on 2017-07-13 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence With Big Data is a pivotal reference for the latest scholarly research on upcoming trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. Featuring extensive coverage on a broad range of topics and perspectives such as deep neural network, domain adaptation modeling, and threat detection, this book is ideally designed for researchers, professionals, and students seeking current research on the latest trends in the field of deep learning techniques in big data analytics.
Book Synopsis Deep Learning: Convergence to Big Data Analytics by : Murad Khan
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 Synopsis Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics by : R. Sujatha
Download or read book Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics written by R. Sujatha and published by CRC Press. This book was released on 2021-09-22 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems. This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval. FEATURES Provides insight into the skill set that leverages one’s strength to act as a good data analyst Discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-making Covers numerous potential applications in healthcare, education, communication, media, and entertainment Offers innovative platforms for integrating Big Data and Deep Learning Presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big Data This book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts.
Book Synopsis Convergence of Cloud with AI for Big Data Analytics by : Danda B. Rawat
Download or read book Convergence of Cloud with AI for Big Data Analytics written by Danda B. Rawat and published by John Wiley & Sons. This book was released on 2023-03-21 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: CONVERGENCE of CLOUD with AI for BIG DATA ANALYTICS This book covers the foundations and applications of cloud computing, AI, and Big Data and analyses their convergence for improved development and services. The 17 chapters of the book masterfully and comprehensively cover the intertwining concepts of artificial intelligence, cloud computing, and big data, all of which have recently emerged as the next-generation paradigms. There has been rigorous growth in their applications and the hybrid blend of AI Cloud and IoT (Ambient-intelligence technology) also relies on input from wireless devices. Despite the multitude of applications and advancements, there are still some limitations and challenges to overcome, such as security, latency, energy consumption, service allocation, healthcare services, network lifetime, etc. Convergence of Cloud with AI for Big Data Analytics: Foundations and Innovation details all these technologies and how they are related to state-of-the-art applications, and provides a comprehensive overview for readers interested in advanced technologies, identifying the challenges, proposed solutions, as well as how to enhance the framework. Audience Researchers and post-graduate students in computing as well as engineers and practitioners in software engineering, electrical engineers, data analysts, and cyber security professionals.
Book Synopsis Convergence of Deep Learning and Artificial Intelligence in Internet of Things by : Ajay Rana
Download or read book Convergence of Deep Learning and Artificial Intelligence in Internet of Things written by Ajay Rana and published by CRC Press. This book was released on 2022-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. • Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. • Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. • Explores the importance of blockchain technology in the Internet of Things security issues. • Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. • Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications. This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.
Book Synopsis Convergence of Blockchain, AI, and IoT by : R. Indrakumari
Download or read book Convergence of Blockchain, AI, and IoT written by R. Indrakumari and published by CRC Press. This book was released on 2021-12-23 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning Techniques and Optimization Strategies in Big Data Analytics by : Thomas, J. Joshua
Download or read book Deep Learning Techniques and Optimization Strategies in Big Data Analytics written by Thomas, J. Joshua and published by IGI Global. This book was released on 2019-11-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Book Synopsis AI and Big Data’s Potential for Disruptive Innovation by : Strydom, Moses
Download or read book AI and Big Data’s Potential for Disruptive Innovation written by Strydom, Moses and published by IGI Global. This book was released on 2019-09-27 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1799804151 Total Pages :1671 pages Book Rating :4.7/5 (998 download)
Book Synopsis Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources
Download or read book Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2019-10-11 with total page 1671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in various real-world applications such as computer vision, image processing, and pattern recognition. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications is a vital reference source that trends in data analytics and potential technologies that will facilitate insight in various domains of science, industry, business, and consumer applications. It also explores the latest concepts, algorithms, and techniques of deep learning and data mining and analysis. Highlighting a range of topics such as natural language processing, predictive analytics, and deep neural networks, this multi-volume book is ideally designed for computer engineers, software developers, IT professionals, academicians, researchers, and upper-level students seeking current research on the latest trends in the field of deep learning.
Book Synopsis Data Science with Semantic Technologies by : Archana Patel
Download or read book Data Science with Semantic Technologies written by Archana Patel and published by CRC Press. This book was released on 2023-06-20 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data is an important asset for any organization, it is essential to apply semantic technologies in data science to fulfill the need of any organization. This first volume of a two-volume handbook set provides a roadmap for new trends and future developments of data science with semantic technologies. Data Science with Semantic Technologies: New Trends and Future Developments highlights how data science enables the user to create intelligence through these technologies. In addition, this book offers the answers to various questions such as: Can semantic technologies facilitate data science? Which type of data science problems can be tackled by semantic technologies? How can data scientists benefit from these technologies? What is the role of semantic technologies in data science? What is the current progress and future of data science with semantic technologies? Which types of problems require the immediate attention of the researchers? What should be the vision 2030 for data science? This volume can serve as an important guide toward applications of data science with semantic technologies for the upcoming generation and, thus, it is a unique resource for scholars, researchers, professionals, and practitioners in this field.
Book Synopsis Intelligent Innovations in Multimedia Data Engineering and Management by : Bhattacharyya, Siddhartha
Download or read book Intelligent Innovations in Multimedia Data Engineering and Management written by Bhattacharyya, Siddhartha and published by IGI Global. This book was released on 2018-09-07 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the ever-increasing volume of data, proper management of data is a challenging proposition to scientists and researchers, and given the vast storage space required, multimedia data is no exception in this regard. Scientists and researchers are investing great effort to discover new space-efficient methods for storage and archiving of this data. Intelligent Innovations in Multimedia Data Engineering and Management provides emerging research exploring the theoretical and practical aspects of storage systems and computing methods for large forms of data. Featuring coverage on a broad range of topics such as binary image, fuzzy logic, and metaheuristic algorithms, this book is ideally designed for computer engineers, IT professionals, technology developers, academicians, and researchers seeking current research on advancing strategies and computing techniques for various types of data.
Book Synopsis Innovations in Machine and Deep Learning by : Gilberto Rivera
Download or read book Innovations in Machine and Deep Learning written by Gilberto Rivera and published by Springer Nature. This book was released on 2023-11-04 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts. The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0. This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.
Book Synopsis Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing by : Velayutham, Sathiyamoorthi
Download or read book Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing written by Velayutham, Sathiyamoorthi and published by IGI Global. This book was released on 2021-01-29 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today’s market, emerging technologies are continually assisting in common workplace practices as companies and organizations search for innovative ways to solve modern issues that arise. Prevalent applications including internet of things, big data, and cloud computing all have noteworthy benefits, but issues remain when separately integrating them into the professional practices. Significant research is needed on converging these systems and leveraging each of their advantages in order to find solutions to real-time problems that still exist. Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing is a pivotal reference source that provides vital research on the relation between these technologies and the impact they collectively have in solving real-world challenges. While highlighting topics such as cloud-based analytics, intelligent algorithms, and information security, this publication explores current issues that remain when attempting to implement these systems as well as the specific applications IoT, big data, and cloud computing have in various professional sectors. This book is ideally designed for academicians, researchers, developers, computer scientists, IT professionals, practitioners, scholars, students, and engineers seeking research on the integration of emerging technologies to solve modern societal issues.
Book Synopsis Handbook of Research on Big Data Storage and Visualization Techniques by : Segall, Richard S.
Download or read book Handbook of Research on Big Data Storage and Visualization Techniques written by Segall, Richard S. and published by IGI Global. This book was released on 2018-01-05 with total page 917 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Book Synopsis Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities by : Usman, Muhammad
Download or read book Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities written by Usman, Muhammad and published by IGI Global. This book was released on 2018-01-26 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis forms the basis of many modes of research ranging from scientific discoveries to governmental findings. With the advent of machine intelligence and neural networks, extracting and modeling, approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities provides emerging information on extraction and prediction patterns in data mining along with knowledge discovery. While highlighting the current issues in data extraction, readers will learn new methodologies comprising of different algorithms that automate the multidimensional schema that remove the manual processes. This book is a vital resource for researchers, academics, and those seeking new information on data mining techniques and trends.
Book Synopsis HPC, Big Data, and AI Convergence Towards Exascale by : Olivier Terzo
Download or read book HPC, Big Data, and AI Convergence Towards Exascale written by Olivier Terzo and published by CRC Press. This book was released on 2022-01-13 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: HPC, Big Data, AI Convergence Towards Exascale provides an updated vision on the most advanced computing, storage, and interconnection technologies, that are at basis of convergence among the HPC, Cloud, Big Data, and artificial intelligence (AI) domains. Through the presentation of the solutions devised within recently founded H2020 European projects, this book provides an insight on challenges faced by integrating such technologies and in achieving performance and energy efficiency targets towards the exascale level. Emphasis is given to innovative ways of provisioning and managing resources, as well as monitoring their usage. Industrial and scientific use cases give to the reader practical examples of the needs for a cross-domain convergence. All the chapters in this book pave the road to new generation of technologies, support their development and, in addition, verify them on real-world problems. The readers will find this book useful because it provides an overview of currently available technologies that fit with the concept of unified Cloud-HPC-Big Data-AI applications and presents examples of their actual use in scientific and industrial applications.
Book Synopsis Visibilities and Invisibilities in Smart Cities: Emerging Research and Opportunities by : McKenna, H. Patricia
Download or read book Visibilities and Invisibilities in Smart Cities: Emerging Research and Opportunities written by McKenna, H. Patricia and published by IGI Global. This book was released on 2021-06-11 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout history, humanity has sought the betterment of its communities. In the 21st century, humanity has technology on its side in the process of improving its cities. Smart cities make their improvements by gathering real-world data in real time. Still, there are many complexities that many do not catch—they are invisible. It is important to understand how people make sense at the urban level and in extra-urban spaces of the combined complexities of invisibilities and visibilities in their environments, interactions, and infrastructures enabled through their own enhanced awareness together with aware technologies that are often embedded, pervasive, and ambient. This book probes the visible and invisible dimensions of emerging understandings of smart cities and regions in the context of more aware people interacting with each other and through more aware and pervasive technologies. Visibilities and Invisibilities in Smart Cities: Emerging Research and Opportunities contributes to the research literature for urban theoretical spaces, methodologies, and applications for smart and responsive cities; the evolving of urban theory and methods for 21st century cities and urbanities; and the formulation of a conceptual framework for associated methodologies and theoretical spaces. This work explores the relationships between variables using a case study approach combined with an explanatory correlational design. It is based on an urban research study conducted from mid-2015 to mid-2020 that spanned multiple countries across three continents. The book is split into four sections: introduction to the concepts of visible and invisible, frameworks for understanding the interplay of the two concepts, associated and evolving theory and methods, and extending current research as opportunities in smart city environments and regions. Covering topics including human geography, smart cities, and urban planning, this book is essential for urban planners, designers, city officials, community agencies, business managers and owners, academicians, researchers, and students, including those who work across multiple domains such as architecture, environmental design, human-computer interaction, human geography, information technology, sociology, and affective computing.
