Deep Learning Innovations And Their Convergence With Big Data

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Deep Learning Innovations and Their Convergence With Big Data

Karthik, S.,Paul, Anand,Karthikeyan, N.
Deep Learning Innovations and Their Convergence With Big Data Book PDF

Author : Karthik, S.,Paul, Anand,Karthikeyan, N.
Publisher : IGI Global
Page : 265 pages
File Size : 53,8 Mb
Release : 2017-07-13
Category : Computers
ISBN : 9781522530169

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Deep Learning Innovations and Their Convergence With Big Data by Karthik, S.,Paul, Anand,Karthikeyan, N. Pdf

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.

Deep Learning: Convergence to Big Data Analytics

Murad Khan,Bilal Jan,Haleem Farman
Deep Learning Convergence to Big Data Analytics Book PDF

Author : Murad Khan,Bilal Jan,Haleem Farman
Publisher : Springer
Page : 79 pages
File Size : 54,8 Mb
Release : 2018-12-30
Category : Computers
ISBN : 9789811334597

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Deep Learning: Convergence to Big Data Analytics by Murad Khan,Bilal Jan,Haleem Farman Pdf

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.

Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics

R. Sujatha,S. L. Aarthy,R. Vettriselvan
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics Book PDF

Author : R. Sujatha,S. L. Aarthy,R. Vettriselvan
Publisher : CRC Press
Page : 216 pages
File Size : 47,6 Mb
Release : 2021-09-22
Category : Technology & Engineering
ISBN : 9781000454536

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Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics by R. Sujatha,S. L. Aarthy,R. Vettriselvan Pdf

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.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book PDF

Author : Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Publisher : IGI Global
Page : 355 pages
File Size : 49,5 Mb
Release : 2019-11-29
Category : Computers
ISBN : 9781799811947

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Deep Learning Techniques and Optimization Strategies in Big Data Analytics by Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian Pdf

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.

Convergence of Cloud with AI for Big Data Analytics

Danda B. Rawat,Lalit K. Awasthi,Valentina Emilia Balas,Mohit Kumar,Jitendra Kumar Samriya
Convergence of Cloud with AI for Big Data Analytics Book PDF

Author : Danda B. Rawat,Lalit K. Awasthi,Valentina Emilia Balas,Mohit Kumar,Jitendra Kumar Samriya
Publisher : John Wiley & Sons
Page : 452 pages
File Size : 53,9 Mb
Release : 2023-02-13
Category : Computers
ISBN : 9781119905219

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Convergence of Cloud with AI for Big Data Analytics by Danda B. Rawat,Lalit K. Awasthi,Valentina Emilia Balas,Mohit Kumar,Jitendra Kumar Samriya Pdf

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.

Convergence of Deep Learning and Artificial Intelligence in Internet of Things

Ajay Rana,Arun Kumar Rana,Sachin Dhawan,Sharad Sharma,Ahmed A Elngar
Convergence of Deep Learning and Artificial Intelligence in Internet of Things Book PDF

Author : Ajay Rana,Arun Kumar Rana,Sachin Dhawan,Sharad Sharma,Ahmed A Elngar
Publisher : CRC Press
Page : 329 pages
File Size : 50,5 Mb
Release : 2022-12-20
Category : Computers
ISBN : 9781000822083

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Convergence of Deep Learning and Artificial Intelligence in Internet of Things by Ajay Rana,Arun Kumar Rana,Sachin Dhawan,Sharad Sharma,Ahmed A Elngar Pdf

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.

Convergence of Blockchain, AI, and IoT

R. Indrakumari,R.Lakshmana Kumar,B. Balusamy,Vijanth Sagayan Asirvadam
Convergence of Blockchain AI and IoT Book PDF

Author : R. Indrakumari,R.Lakshmana Kumar,B. Balusamy,Vijanth Sagayan Asirvadam
Publisher : CRC Press
Page : 206 pages
File Size : 43,8 Mb
Release : 2021-12-23
Category : Technology & Engineering
ISBN : 9781000519327

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Convergence of Blockchain, AI, and IoT by R. Indrakumari,R.Lakshmana Kumar,B. Balusamy,Vijanth Sagayan Asirvadam Pdf

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.

Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications

Management Association, Information Resources
Deep Learning and Neural Networks Concepts Methodologies Tools and Applications Book PDF

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 1671 pages
File Size : 44,7 Mb
Release : 2019-10-11
Category : Computers
ISBN : 9781799804154

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Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf

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.

Intelligent Innovations in Multimedia Data Engineering and Management

Bhattacharyya, Siddhartha
Intelligent Innovations in Multimedia Data Engineering and Management Book PDF

Author : Bhattacharyya, Siddhartha
Publisher : IGI Global
Page : 316 pages
File Size : 46,9 Mb
Release : 2018-09-07
Category : Computers
ISBN : 9781522571087

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Intelligent Innovations in Multimedia Data Engineering and Management by Bhattacharyya, Siddhartha Pdf

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.

Innovations in Machine and Deep Learning

Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez
Innovations in Machine and Deep Learning Book PDF

Author : Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez
Publisher : Springer Nature
Page : 506 pages
File Size : 47,5 Mb
Release : 2023-11-04
Category : Computers
ISBN : 9783031406881

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Innovations in Machine and Deep Learning by Gilberto Rivera,Alejandro Rosete,Bernabé Dorronsoro,Nelson Rangel-Valdez Pdf

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.

Data Science with Semantic Technologies

Archana Patel,Narayan C. Debnath
Data Science with Semantic Technologies Book PDF

Author : Archana Patel,Narayan C. Debnath
Publisher : CRC Press
Page : 293 pages
File Size : 49,5 Mb
Release : 2023-06-20
Category : Computers
ISBN : 9781000881233

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Data Science with Semantic Technologies by Archana Patel,Narayan C. Debnath Pdf

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.

Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing

Velayutham, Sathiyamoorthi
Challenges and Opportunities for the Convergence of IoT Big Data and Cloud Computing Book PDF

Author : Velayutham, Sathiyamoorthi
Publisher : IGI Global
Page : 350 pages
File Size : 43,7 Mb
Release : 2021-01-29
Category : Computers
ISBN : 9781799831136

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Challenges and Opportunities for the Convergence of IoT, Big Data, and Cloud Computing by Velayutham, Sathiyamoorthi Pdf

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.

Handbook of Research on Big Data Storage and Visualization Techniques

Segall, Richard S.,Cook, Jeffrey S.
Handbook of Research on Big Data Storage and Visualization Techniques Book PDF

Author : Segall, Richard S.,Cook, Jeffrey S.
Publisher : IGI Global
Page : 917 pages
File Size : 46,8 Mb
Release : 2018-01-05
Category : Computers
ISBN : 9781522531432

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Handbook of Research on Big Data Storage and Visualization Techniques by Segall, Richard S.,Cook, Jeffrey S. Pdf

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.

Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities

Usman, Muhammad,Usman, M.
Predictive Analysis on Large Data for Actionable Knowledge Emerging Research and Opportunities Book PDF

Author : Usman, Muhammad,Usman, M.
Publisher : IGI Global
Page : 177 pages
File Size : 53,5 Mb
Release : 2018-01-26
Category : Computers
ISBN : 9781522550303

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Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities by Usman, Muhammad,Usman, M. Pdf

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.

AI and Big Data’s Potential for Disruptive Innovation

Strydom, Moses,Buckley, Sheryl
AI and Big Data s Potential for Disruptive Innovation Book PDF

Author : Strydom, Moses,Buckley, Sheryl
Publisher : IGI Global
Page : 405 pages
File Size : 49,7 Mb
Release : 2019-09-27
Category : Computers
ISBN : 9781522596899

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AI and Big Data’s Potential for Disruptive Innovation by Strydom, Moses,Buckley, Sheryl Pdf

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.