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.

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.

Download or read book Machine Learning Models and Algorithms for Big Data Classification written by Shan Suthaharan and published by Springer. This book was released on 2015-10-20 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Download or read book Deep Learning in Data Analytics written by Debi Prasanna Acharjya and published by Springer Nature. This book was released on 2021-08-11 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.

Download or read book Advanced Deep Learning Applications in Big Data Analytics written by Bouarara, Hadj Ahmed and published by IGI Global. This book was released on 2020-10-16 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.

Download or read book Big Data Analysis for Green Computing written by Rohit Sharma and published by CRC Press. This book was released on 2021-10-29 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

Download or read book Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-12-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Download or read book Soft Computing Theories and Applications written by Rajesh Kumar and published by Springer Nature. This book was released on 2023-04-24 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and health care, to supply chain management, image processing and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2022), held at University Institute of Technology, Himachal Pradesh University Shimla, Himachal Pradesh, India. The book offers valuable insights into soft computing for teachers and researchers alike; the book inspires further research in this dynamic field.

Download or read book Third Congress on Intelligent Systems written by Sandeep Kumar and published by Springer Nature. This book was released on 2023-05-18 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of selected papers presented at the Third Congress on Intelligent Systems (CIS 2022), organized by CHRIST (Deemed to be University), Bangalore, India, under the technical sponsorship of the Soft Computing Research Society, India, during September 5–6, 2022. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as the Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber-physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision-making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human-computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro-fuzzy systems.

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.

Download or read book Artificial Intelligence and Cybersecurity written by Ishaani Priyadarshini and published by CRC Press. This book was released on 2022-02-04 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and cybersecurity are two emerging fields that have made phenomenal contributions toward technological advancement. As cyber-attacks increase, there is a need to identify threats and thwart attacks. This book incorporates recent developments that artificial intelligence brings to the cybersecurity world. Artificial Intelligence and Cybersecurity: Advances and Innovations provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems. This edited book provides a premier interdisciplinary platform for researchers, practitioners and educators. It presents and discusses the most recent innovations, trends and concerns as well as practical challenges and solutions adopted in the fields of artificial intelligence and cybersecurity.

Download or read book ICT and Data Sciences written by Archana Singh and published by CRC Press. This book was released on 2022-05-15 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the state-of-the-art research on data usage, security, and privacy in the scenarios of the Internet of Things (IoT), along with related applications using Machine Learning and Big Data technologies to design and make efficient Internet-compatible IoT systems. ICT and Data Sciences brings together IoT and Machine Learning and provides the careful integration of both, along with many examples and case studies. It illustrates the merging of two technologies while presenting basic to high-level concepts covering different fields and domains such as the Hospitality and Tourism industry, Smart Clothing, Cyber Crime, Programming, Communications, Business Intelligence, all in the context of the Internet of Things. The book is written for researchers and practitioners, working in Information Communication Technology and Computer Science.

Download or read book MULTIPLY BUSINESS RESULTS WITH ARTIFICIAL INTELLIGENCE written by DAVID SANDUA and published by . This book was released on 2023-09-04 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an increasingly competitive and dynamic business world, artificial intelligence (AI) is the catalyst that can multiply your results. This book is an essential guide that will take you by the hand to understand how AI can transform every corner of your business. From automating routine tasks and freeing up your employees' time to using predictive analytics to optimize the supply chain, AI becomes an invaluable tool. The book also addresses how AI can improve data-driven decision making, enabling companies to identify growth opportunities and potential risks with never-before-seen accuracy. In the realm of customer service, you'll discover how chatbots and AI algorithms can personalize interactions, elevating customer satisfaction and thereby increasing sales. In addition, it does not skirt the ethical and privacy challenges that come with AI adoption, offering strategies for ethical and secure use of data. It also addresses the skills and talent gaps in AI adoption, providing strategies for fostering a culture of AI adoption in your company. If you are looking for a competitive advantage and aspire to exponential growth, this book is your map to the future. It gives you not only an overview of the AI landscape in business, but also practical and actionable strategies for implementing AI in your company effectively. In short, it's a must-read for any business leader who wants to be at the forefront of the technology revolution.

Download or read book Handbook of Sustainable Development Through Green Engineering and Technology written by Vikram Bali and published by CRC Press. This book was released on 2022-09-27 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Green engineering involves the designing, innovation, and commercialization of products and processes which promote sustainability without eliminating both efficiency and economic viability. This handbook focuses on sustainable development through green engineering and technology. It is intended to address the applications and issues involved in their practical implementation. A new range of renewable-energy technologies, modified to provide green engineering, will be described in this handbook. It will explore all green technologies required to provide green engineering for the future.These include, but are not limited to, green smart buildings, fuel-efficient transportation, paperless offices, and many more energy-efficient measures. Handbook of Sustainable Development through Green Engineering and Technology acts as a comprehensive reference book to use when identifying development for programs and sustainable initiatives within the current legislative framework. It aims to be of great interest to researchers, faculty members, and students across the globe.

Download or read book Green Computing in Network Security written by Deepak Kumar Sharma and published by CRC Press. This book was released on 2022-01-10 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on green computing-based network security techniques and addresses the challenges involved in practical implementation. It also explores the idea of energy-efficient computing for network and data security and covers the security threats involved in social networks, data centers, IoT, and biomedical applications. Green Computing in Network Security: Energy Efficient Solutions for Business and Home includes analysis of green-security mechanisms and explores the role of green computing for secured modern internet applications. It discusses green computing-based distributed learning approaches for security and emphasizes the development of green computing-based security systems for IoT devices. Written with researchers, academic libraries, and professionals in mind so they can get up to speed on network security, the challenges, and implementation processes.

Download or read book Handbook of Green Computing and Blockchain Technologies written by Kavita Saini and published by CRC Press. This book was released on 2021-12-27 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides a computational perspective on green computing and blockchain technologies. It presents not only how to identify challenges using a practical approach but also how to develop strategies for addressing industry challenges. Handbook of Green Computing and Blockchain Technologies takes a practical-oriented approach, including solved examples and highlights standardization, industry bodies, and initiatives. Case studies provide a deeper understanding of blockchain and are related to real-time scenarios. The handbook analyzes current research and development in green computing and blockchain analytics, studies existing related standards and technologies, and provides results on implementation, challenges, and issues in today’s society. FEATURES Analyzes current research developments in green computing and blockchain analytics Provides an analysis of implementation challenges and solutions Offers innovations in the decentralization process for the application of blockchain in areas such as healthcare, government services, agriculture, supply chain, financial, ecommerce, and more Discusses the impact of this technology on people’s lives, the way they work and learn, and highlights standardization, industry bodies, and initiatives This handbook will benefit researchers, software developers, and undergraduate and postgraduate students in industrial systems, manufacturing, information technology, computer science, manufacturing, communications, and electrical engineering.

Download or read book Deep Learning Technologies for the Sustainable Development Goals written by Virender Kadyan and published by Springer Nature. This book was released on 2023-02-01 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.