Noise Filtering For Big Data Analytics

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Noise Filtering for Big Data Analytics

Author : Souvik Bhattacharyya
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110697262
Total Pages : 195 pages
Book Rating : 4.1/5 (16 download)

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Book Synopsis Noise Filtering for Big Data Analytics by : Souvik Bhattacharyya

Download or read book Noise Filtering for Big Data Analytics written by Souvik Bhattacharyya and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-06-21 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

Big Data Preprocessing

Author : Julián Luengo
Publisher : Springer Nature
ISBN 13 : 3030391051
Total Pages : 193 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Big Data Preprocessing by : Julián Luengo

Download or read book Big Data Preprocessing written by Julián Luengo and published by Springer Nature. This book was released on 2020-03-16 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud. Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems. Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book.

The Internet of Things and Big Data Analytics

Author : Pethuru Raj
Publisher : CRC Press
ISBN 13 : 1000057399
Total Pages : 328 pages
Book Rating : 4.0/5 ( download)

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Book Synopsis The Internet of Things and Big Data Analytics by : Pethuru Raj

Download or read book The Internet of Things and Big Data Analytics written by Pethuru Raj and published by CRC Press. This book was released on 2020-06-07 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively conveys the theoretical and practical aspects of IoT and big data analytics with the solid contributions from practitioners as well as academicians. This book examines and expounds the unique capabilities of the big data analytics platforms in capturing, cleansing and crunching IoT device/sensor data in order to extricate actionable insights. A number of experimental case studies and real-world scenarios are incorporated in this book in order to instigate our book readers. This book Analyzes current research and development in the domains of IoT and big data analytics Gives an overview of latest trends and transitions happening in the IoT data analytics space Illustrates the various platforms, processes, patterns, and practices for simplifying and streamlining IoT data analytics The Internet of Things and Big Data Analytics: Integrated Platforms and Industry Use Cases examines and accentuates how the multiple challenges at the cusp of IoT and big data can be fully met. The device ecosystem is growing steadily. It is forecast that there will be billions of connected devices in the years to come. When these IoT devices, resource-constrained as well as resource-intensive, interact with one another locally and remotely, the amount of multi-structured data generated, collected, and stored is bound to grow exponentially. Another prominent trend is the integration of IoT devices with cloud-based applications, services, infrastructures, middleware solutions, and databases. This book examines the pioneering technologies and tools emerging and evolving in order to collect, pre-process, store, process and analyze data heaps in order to disentangle actionable insights.

Big Data Analytics Methods

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1547401567
Total Pages : 254 pages
Book Rating : 4.5/5 (474 download)

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Big Data Analytics Techniques for Market Intelligence

Author : Darwish, Dina
Publisher : IGI Global
ISBN 13 :
Total Pages : 536 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Big Data Analytics Techniques for Market Intelligence by : Darwish, Dina

Download or read book Big Data Analytics Techniques for Market Intelligence written by Darwish, Dina and published by IGI Global. This book was released on 2024-01-04 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field.

Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

Author : Aboul Ella Hassanien
Publisher : Springer Nature
ISBN 13 : 303059338X
Total Pages : 648 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges by : Aboul Ella Hassanien

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.

Big Data Analytics for Cyber-Physical System in Smart City

Author : Mohammed Atiquzzaman
Publisher : Springer Nature
ISBN 13 : 9811525684
Total Pages : 2049 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Big Data Analytics for Cyber-Physical System in Smart City by : Mohammed Atiquzzaman

Download or read book Big Data Analytics for Cyber-Physical System in Smart City written by Mohammed Atiquzzaman and published by Springer Nature. This book was released on 2020-01-11 with total page 2049 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the first Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019) conference, held in Shengyang, China, on 28–29 December 2019. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Advanced Mathematical Applications in Data Science

Author : Biswadip Basu Mallik
Publisher : Bentham Science Publishers
ISBN 13 : 9815124854
Total Pages : 223 pages
Book Rating : 4.8/5 (151 download)

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Book Synopsis Advanced Mathematical Applications in Data Science by : Biswadip Basu Mallik

Download or read book Advanced Mathematical Applications in Data Science written by Biswadip Basu Mallik and published by Bentham Science Publishers. This book was released on 2023-08-24 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of data science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in data science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, machine learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. Key Features: Comprehensive coverage of advanced mathematical concepts and techniques in data science Contributions from established scientists, researchers, and academicians Real-world case studies and practical applications of mathematical methods Focus on diverse areas, such as image classification, carbon emission assessment, customer churn prediction, and healthcare data analysis In-depth exploration of data science's connection with mathematics, computer science, and artificial intelligence Scholarly references for each chapter Suitable for readers with high school-level mathematical knowledge, making it accessible to a broad audience in academia and industry.

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

Author : John Macintyre
Publisher : Springer Nature
ISBN 13 : 3030895114
Total Pages : 999 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John Macintyre

Download or read book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John Macintyre and published by Springer Nature. This book was released on 2021-11-02 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Data Fabric Architectures

Author : Vandana Sharma
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3111000885
Total Pages : 228 pages
Book Rating : 4.1/5 (11 download)

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Book Synopsis Data Fabric Architectures by : Vandana Sharma

Download or read book Data Fabric Architectures written by Vandana Sharma and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-05-22 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Big Data Analytics Methods

Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 1547401583
Total Pages : 282 pages
Book Rating : 4.5/5 (474 download)

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Book Synopsis Big Data Analytics Methods by : Peter Ghavami

Download or read book Big Data Analytics Methods written by Peter Ghavami and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-12-16 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Big Data Analytics in Cognitive Social Media and Literary Texts

Author : Sanjiv Sharma
Publisher : Springer Nature
ISBN 13 : 9811647291
Total Pages : 316 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Big Data Analytics in Cognitive Social Media and Literary Texts by : Sanjiv Sharma

Download or read book Big Data Analytics in Cognitive Social Media and Literary Texts written by Sanjiv Sharma and published by Springer Nature. This book was released on 2021-10-10 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Big Data Analytics in Earth, Atmospheric, and Ocean Sciences

Author : Thomas Huang
Publisher : John Wiley & Sons
ISBN 13 : 1119467535
Total Pages : 356 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Big Data Analytics in Earth, Atmospheric, and Ocean Sciences by : Thomas Huang

Download or read book Big Data Analytics in Earth, Atmospheric, and Ocean Sciences written by Thomas Huang and published by John Wiley & Sons. This book was released on 2022-10-14 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applying tools for data analysis to the rapidly increasing volume of data about the Earth An ever-increasing volume of Earth data is being gathered. These data are “big” not only in size but also in their complexity, different formats, and varied scientific disciplines. As such, big data are disrupting traditional research. New methods and platforms, such as the cloud, are tackling these new challenges. Big Data Analytics in Earth, Atmospheric, and Ocean Sciences explores new tools for the analysis and display of the rapidly increasing volume of data about the Earth. Volume highlights include: An introduction to the breadth of big earth data analytics Architectures developed to support big earth data analytics Different analysis and statistical methods for big earth data Current applications of analytics to Earth science data Challenges to fully implementing big data analytics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. Find out more in this Q&A with the editors.

E-Commerce Big Data Mining and Analytics

Author : Jie Cao
Publisher : Springer Nature
ISBN 13 : 9819935881
Total Pages : 217 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis E-Commerce Big Data Mining and Analytics by : Jie Cao

Download or read book E-Commerce Big Data Mining and Analytics written by Jie Cao and published by Springer Nature. This book was released on 2023 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to give readers with a preliminary but critical introduction and summary of e-commerce and big data analysis. This book introduces how to achieve data acquisition and pre-processing. Specifically, this book provides three representative and interesting scenarios to demonstrate the application of e-commerce and big data analysis, i.e., trajectory big data mining technology, e-commerce fraud and anti-fraud, and recommendation system. Also this book provides the basic and illustrative operation steps of python programming language for e-commerce and big data analysis. By reading this book, readers can learn the basic concepts and principles of e-commerce and big data analysis.

Research Practitioner's Handbook on Big Data Analytics

Author : S. Sasikala
Publisher : CRC Press
ISBN 13 : 1000578364
Total Pages : 310 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Research Practitioner's Handbook on Big Data Analytics by : S. Sasikala

Download or read book Research Practitioner's Handbook on Big Data Analytics written by S. Sasikala and published by CRC Press. This book was released on 2023-05-04 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies. The book gives the why and the how of big data analytics in an organized and straightforward manner, using both theoretical and practical approaches. The book’s authors have organized the contents in a systematic manner, starting with an introduction and overview of big data analytics and then delving into pre-processing methods, feature selection methods and algorithms, big data streams, and big data classification. Such terms and methods as swarm intelligence, data mining, the bat algorithm and genetic algorithms, big data streams, and many more are discussed. The authors explain how deep learning and machine learning along with other methods and tools are applied in big data analytics. The last section of the book presents a selection of illustrative case studies that show examples of the use of data analytics in industries such as health care, business, education, and social media.

Software Project Management

Author : Moh’d A. Radaideh
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3111206866
Total Pages : 536 pages
Book Rating : 4.1/5 (112 download)

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Book Synopsis Software Project Management by : Moh’d A. Radaideh

Download or read book Software Project Management written by Moh’d A. Radaideh and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-12-18 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Project Management (SPM) differs from the Traditional Project Management (PM) approaches in that Software Engineering requires multiple rounds of Software Testing, and Updating in accordance with their Testing results and their customer’s feedback. Thus, SPM introduces unique life cycle processes.This book presents an introduction and a critical analysis of the main Software Project Management Frameworks, and offers the author’s original approach to SPM as developed by him over years of professional and teaching experience in the Academia and the IT/Software Industry. It also provides Executive Summaries of the Project Management and Software Project Management Perspectives offered by the Project Management Institute (PMI), the IEEE-Computer Society (IEEE-CS), and the SCRUM Project Management Bodies such as the SCRUMstudy.

Interactive Mobile Communication Technologies and Learning

Author : Michael E. Auer
Publisher : Springer
ISBN 13 : 3319751751
Total Pages : 980 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Interactive Mobile Communication Technologies and Learning by : Michael E. Auer

Download or read book Interactive Mobile Communication Technologies and Learning written by Michael E. Auer and published by Springer. This book was released on 2018-02-13 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interactive mobile technologies have now become the core of many—if not all—fields of society. Not only do the younger generation of students expect a mobile working and learning environment, but also the new ideas, technologies and solutions introduced on a nearly daily basis also boost this trend. Discussing and assessing key trends in the mobile field were the primary aims of the 11th International Conference on Interactive Mobile Communication, Technologies and Learning (IMCL2017), which was held in Thessaloniki from 30 November to 01 December 2017. Since being founded in 2006, the conference has been devoted to new approaches in interactive mobile technologies, with a focus on learning. The IMCL conferences have in the meanwhile become a central forum of the exchange of new research results and relevant trends, as well as best practices. This book contains papers in the fields of: Future Trends and Emerging Mobile Technologies Design and Development of Mobile Learning Apps and Content Mobile Games—Gamification and Mobile Learning Adaptive Mobile Environments Augmented Reality and Immersive Applications Tangible, Embedded and Embodied Interaction Interactive Collaborative and Blended Learning Digital Technology in Sports Mobile Health Care and Training Multimedia Learning in Music Education 5G Network Infrastructure Case Studies Real-World Experiences The content will appeal to a broad readership, including policymakers, academics, educators, researchers in pedagogy and learning theory, school teachers, the learning industry, further education lecturers, etc.