Big Data In Engineering Applications

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Big Data in Engineering Applications

Author : Sanjiban Sekhar Roy
Publisher : Springer
ISBN 13 : 9811084769
Total Pages : 381 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Big Data in Engineering Applications by : Sanjiban Sekhar Roy

Download or read book Big Data in Engineering Applications written by Sanjiban Sekhar Roy and published by Springer. This book was released on 2018-05-02 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas.

Big Data Application in Power Systems

Author : Reza Arghandeh
Publisher : Elsevier
ISBN 13 : 0443219516
Total Pages : 450 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Big Data Application in Power Systems by : Reza Arghandeh

Download or read book Big Data Application in Power Systems written by Reza Arghandeh and published by Elsevier. This book was released on 2024-07-01 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Application in Power Systems, Second Edition presents a thorough update of the previous volume, providing readers with step-by-step guidance in big data analytics utilization for power system diagnostics, operation, and control. Bringing back a team of global experts and drawing on fresh, emerging perspectives, this book provides cutting-edge advice for meeting today's challenges in this rapidly accelerating area of power engineering. Divided into three parts, this book begins by breaking down the big picture for electric utilities, before zooming in to examine theoretical problems and solutions in detail. Finally, the third section provides case studies and applications, demonstrating solution troubleshooting and design from a variety of perspectives and for a range of technologies. Readers will develop new strategies and techniques for leveraging data towards real-world outcomes. Including five brand new chapters on emerging technological solutions, Big Data Application in Power Systems, Second Edition remains an essential resource for the reader aiming to utilize the potential of big data in the power systems of the future. - Provides a total refresh to include the most up-to-date research, developments, and challenges - Focuses on practical techniques, including rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches for processing high dimensional, heterogeneous, and spatiotemporal data - Engages with cross-disciplinary lessons, drawing on the impact of intersectional technology including statistics, computer science, and bioinformatics - Includes five brand new chapters on hot topics, ranging from uncertainty decision-making to features, selection methods, and the opportunities provided by social network data

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Author : Arun Kumar Sangaiah
Publisher : Academic Press
ISBN 13 : 0128133279
Total Pages : 364 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications by : Arun Kumar Sangaiah

Download or read book Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications written by Arun Kumar Sangaiah and published by Academic Press. This book was released on 2018-08-21 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. - Presents a brief overview of computational intelligence paradigms and its significant role in application domains - Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches - Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing - Provides new advances in the fields of CI for bio-engineering application

Big Data Analytics in Supply Chain Management

Author : Iman Rahimi
Publisher : CRC Press
ISBN 13 : 1000326918
Total Pages : 211 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Big Data Analytics in Supply Chain Management by : Iman Rahimi

Download or read book Big Data Analytics in Supply Chain Management written by Iman Rahimi and published by CRC Press. This book was released on 2020-12-20 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

Data Mining for Scientific and Engineering Applications

Author : R.L. Grossman
Publisher : Springer Science & Business Media
ISBN 13 : 9781402001147
Total Pages : 632 pages
Book Rating : 4.0/5 (11 download)

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Book Synopsis Data Mining for Scientific and Engineering Applications by : R.L. Grossman

Download or read book Data Mining for Scientific and Engineering Applications written by R.L. Grossman and published by Springer Science & Business Media. This book was released on 2001-10-31 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Computational and Statistical Methods for Analysing Big Data with Applications

Author : Shen Liu
Publisher : Academic Press
ISBN 13 : 0081006519
Total Pages : 208 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Computational and Statistical Methods for Analysing Big Data with Applications by : Shen Liu

Download or read book Computational and Statistical Methods for Analysing Big Data with Applications written by Shen Liu and published by Academic Press. This book was released on 2015-11-20 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate

Industrial Engineering in the Big Data Era

Author : Fethi Calisir
Publisher : Springer
ISBN 13 : 3030033171
Total Pages : 500 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Industrial Engineering in the Big Data Era by : Fethi Calisir

Download or read book Industrial Engineering in the Big Data Era written by Fethi Calisir and published by Springer. This book was released on 2019-01-23 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held in Nevsehir, Turkey, on June 21-22, 2018. They reports on industrial engineering methods and applications, with a special focus on the advantages and challenges posed by Big data in this field. The book covers a wide range of topics, including decision making, optimization, supply chain management and quality control.

Big Data

Author : James Warren
Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Big Data by : James Warren

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Mathematics of Big Data

Author : Jeremy Kepner
Publisher : MIT Press
ISBN 13 : 0262347911
Total Pages : 443 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Mathematics of Big Data by : Jeremy Kepner

Download or read book Mathematics of Big Data written by Jeremy Kepner and published by MIT Press. This book was released on 2018-08-07 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools—including spreadsheets, databases, matrices, and graphs—developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.

AI for Big Data-Based Engineering Applications from Security Perspectives

Author : Balwinder Raj
Publisher : CRC Press
ISBN 13 : 1000901505
Total Pages : 261 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis AI for Big Data-Based Engineering Applications from Security Perspectives by : Balwinder Raj

Download or read book AI for Big Data-Based Engineering Applications from Security Perspectives written by Balwinder Raj and published by CRC Press. This book was released on 2023-06-30 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI), machine learning, and advanced electronic circuits involve learning from every data input and using those inputs to generate new rules for future business analytics. AI and machine learning are now giving us new opportunities to use big data that we already had, as well as unleash a whole lot of new use cases with new data types. With the increasing use of AI dealing with highly sensitive information such as healthcare, adequate security measures are required to securely store and transmit this information. This book provides a broader coverage of the basic aspects of advanced circuits design and applications. AI for Big Data-Based Engineering Applications from Security Perspectives is an integrated source that aims at understanding the basic concepts associated with the security of advanced circuits. The content includes theoretical frameworks and recent empirical findings in the field to understand the associated principles, key challenges, and recent real-time applications of advanced circuits, AI, and big data security. It illustrates the notions, models, and terminologies that are widely used in the area of Very Large Scale Integration (VLSI) circuits, security, identifies the existing security issues in the field, and evaluates the underlying factors that influence system security. This work emphasizes the idea of understanding the motivation behind advanced circuit design to establish the AI interface and to mitigate security attacks in a better way for big data. This book also outlines exciting areas of future research where already existing methodologies can be implemented. This material is suitable for students, researchers, and professionals with research interest in AI for big data–based engineering applications, faculty members across universities, and software developers.

Software Engineering in IoT, Big Data, Cloud and Mobile Computing

Author : Haengkon Kim
Publisher : Springer Nature
ISBN 13 : 3030647730
Total Pages : 225 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Software Engineering in IoT, Big Data, Cloud and Mobile Computing by : Haengkon Kim

Download or read book Software Engineering in IoT, Big Data, Cloud and Mobile Computing written by Haengkon Kim and published by Springer Nature. This book was released on 2020-12-26 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book presents scientific results of the International Semi-Virtual Workshop on Software Engineering in IoT, Big data, Cloud and Mobile Computing (SE-ICBM 2020) which was held on October 15, 2020, at Soongsil University, Seoul, Korea. The aim of this workshop was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The workshop organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 17 of the conference’s most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

Big Data, Cloud Computing, Data Science & Engineering

Author : Roger Lee
Publisher : Springer
ISBN 13 : 3319968033
Total Pages : 196 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Big Data, Cloud Computing, Data Science & Engineering by : Roger Lee

Download or read book Big Data, Cloud Computing, Data Science & Engineering written by Roger Lee and published by Springer. This book was released on 2018-08-13 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10–12, 2018 in Kanazawa. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way. All aspects (theory, applications and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here. The conference organizers selected the best papers from among those accepted for presentation. The papers were chosen on the basis of review scores submitted by members of the program committee and subsequently underwent further rigorous review. Following this second round of review, 13 of the conference’s most promising papers were selected for this Springer (SCI) book. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.

Research Anthology on Big Data Analytics, Architectures, and Applications

Author : Information Resources Management Association
Publisher : Engineering Science Reference
ISBN 13 : 9781668436622
Total Pages : 0 pages
Book Rating : 4.4/5 (366 download)

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Book Synopsis Research Anthology on Big Data Analytics, Architectures, and Applications by : Information Resources Management Association

Download or read book Research Anthology on Big Data Analytics, Architectures, and Applications written by Information Resources Management Association and published by Engineering Science Reference. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Big Data: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1466698411
Total Pages : 2523 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Big Data: Concepts, Methodologies, Tools, and Applications by : Management Association, Information Resources

Download or read book Big Data: Concepts, Methodologies, Tools, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2016-04-20 with total page 2523 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. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Signal Processing and Networking for Big Data Applications

Author : Zhu Han
Publisher : Cambridge University Press
ISBN 13 : 1108155944
Total Pages : 375 pages
Book Rating : 4.1/5 (81 download)

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Book Synopsis Signal Processing and Networking for Big Data Applications by : Zhu Han

Download or read book Signal Processing and Networking for Big Data Applications written by Zhu Han and published by Cambridge University Press. This book was released on 2017-04-27 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

Nonlinear Approaches in Engineering Applications

Author : Reza N. Jazar
Publisher : Springer
ISBN 13 : 3030189635
Total Pages : 486 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Nonlinear Approaches in Engineering Applications by : Reza N. Jazar

Download or read book Nonlinear Approaches in Engineering Applications written by Reza N. Jazar and published by Springer. This book was released on 2019-08-06 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the latest applications of nonlinear approaches in engineering and addresses a range of scientific problems. Examples focus on issues in automotive technology, including automotive dynamics, control for electric and hybrid vehicles, and autodriver algorithm for autonomous vehicles. Also included are discussions on renewable energy plants, data modeling, driver-aid methods, and low-frequency vibration. Chapters are based on invited contributions from world-class experts who advance the future of engineering by discussing the development of more optimal, accurate, efficient, cost, and energy effective systems. This book is appropriate for researchers, students, and practising engineers who are interested in the applications of nonlinear approaches to solving engineering and science problems. Presents a broad range of practical topics and approaches; Explains approaches to better, safer, and cheaper systems; Emphasises automotive applications, physical meaning, and methodologies.

Machine Learning and Big Data

Author : Uma N. Dulhare
Publisher : John Wiley & Sons
ISBN 13 : 1119654742
Total Pages : 544 pages
Book Rating : 4.1/5 (196 download)

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Book Synopsis Machine Learning and Big Data by : Uma N. Dulhare

Download or read book Machine Learning and Big Data written by Uma N. Dulhare and published by John Wiley & Sons. This book was released on 2020-09-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.