Handbook Of Research On Big Data Clustering And Machine Learning

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Handbook of Research on Big Data Clustering and Machine Learning

Garcia Marquez, Fausto Pedro
Handbook of Research on Big Data Clustering and Machine Learning Book PDF

Author : Garcia Marquez, Fausto Pedro
Publisher : IGI Global
Page : 478 pages
File Size : 52,5 Mb
Release : 2019-10-04
Category : Computers
ISBN : 9781799801078

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Handbook of Research on Big Data Clustering and Machine Learning by Garcia Marquez, Fausto Pedro Pdf

As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary. The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.

Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics

Patil, Bhushan,Vohra, Manisha
Handbook of Research on Engineering Business and Healthcare Applications of Data Science and Analytics Book PDF

Author : Patil, Bhushan,Vohra, Manisha
Publisher : IGI Global
Page : 583 pages
File Size : 54,8 Mb
Release : 2020-10-23
Category : Computers
ISBN : 9781799830542

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Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics by Patil, Bhushan,Vohra, Manisha Pdf

Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.

Handbook of Research for Big Data

Vivek Kumar,Sanjaya Kumar Panda,Prayag Tiwari
Handbook of Research for Big Data Book PDF

Author : Vivek Kumar,Sanjaya Kumar Panda,Prayag Tiwari
Publisher : Unknown
Page : 375 pages
File Size : 50,7 Mb
Release : 2022
Category : Big data
ISBN : 1771889802

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Handbook of Research for Big Data by Vivek Kumar,Sanjaya Kumar Panda,Prayag Tiwari Pdf

This book helps to meet the challenge of managing and using Big Data by presenting new research on various technological advances in the field.

Data Clustering

Charu C. Aggarwal,Chandan K. Reddy
Data Clustering Book PDF

Author : Charu C. Aggarwal,Chandan K. Reddy
Publisher : CRC Press
Page : 654 pages
File Size : 51,5 Mb
Release : 2018-09-03
Category : Business & Economics
ISBN : 9781315360416

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Data Clustering by Charu C. Aggarwal,Chandan K. Reddy Pdf

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.

Big Data Analysis: New Algorithms for a New Society

Nathalie Japkowicz,Jerzy Stefanowski
Big Data Analysis New Algorithms for a New Society Book PDF

Author : Nathalie Japkowicz,Jerzy Stefanowski
Publisher : Springer
Page : 329 pages
File Size : 45,5 Mb
Release : 2015-12-16
Category : Technology & Engineering
ISBN : 9783319269894

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Big Data Analysis: New Algorithms for a New Society by Nathalie Japkowicz,Jerzy Stefanowski Pdf

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.

Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science

Panda, Mrutyunjaya,Misra, Harekrishna
Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science Book PDF

Author : Panda, Mrutyunjaya,Misra, Harekrishna
Publisher : IGI Global
Page : 392 pages
File Size : 45,5 Mb
Release : 2021-01-08
Category : Computers
ISBN : 9781799866619

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Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science by Panda, Mrutyunjaya,Misra, Harekrishna Pdf

In today’s digital world, the huge amount of data being generated is unstructured, messy, and chaotic in nature. Dealing with such data, and attempting to unfold the meaningful information, can be a challenging task. Feature engineering is a process to transform such data into a suitable form that better assists with interpretation and visualization. Through this method, the transformed data is more transparent to the machine learning models, which in turn causes better prediction and analysis of results. Data science is crucial for the data scientist to assess the trade-offs of their decisions regarding the effectiveness of the machine learning model implemented. Investigating the demand in this area today and in the future is a necessity. The Handbook of Research on Automated Feature Engineering and Advanced Applications in Data Science provides an in-depth analysis on both the theoretical and the latest empirical research findings on how features can be extracted and transformed from raw data. The chapters will introduce feature engineering and the recent concepts, methods, and applications with the use of various data types, as well as examine the latest machine learning applications on the data. While highlighting topics such as detection, tracking, selection techniques, and prediction models using data science, this book is ideally intended for research scholars, big data scientists, project developers, data analysts, and computer scientists along with practitioners, researchers, academicians, and students interested in feature engineering and its impact on data.

Applications of Machine Learning in Big-Data Analytics and Cloud Computing

Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Applications of Machine Learning in Big Data Analytics and Cloud Computing Book PDF

Author : Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt
Publisher : CRC Press
Page : 346 pages
File Size : 51,8 Mb
Release : 2022-09-01
Category : Technology & Engineering
ISBN : 9781000793550

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Applications of Machine Learning in Big-Data Analytics and Cloud Computing by Subhendu Kumar Pani,Somanath Tripathy,George Jandieri,Sumit Kundu,Talal Ashraf Butt Pdf

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

Handbook of Big Data Analytics

Vadlamani Ravi,Aswani Kumar Cherukuri
Handbook of Big Data Analytics Book PDF

Author : Vadlamani Ravi,Aswani Kumar Cherukuri
Publisher : IET
Page : 419 pages
File Size : 41,6 Mb
Release : 2021-07-09
Category : Computers
ISBN : 9781839530593

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Handbook of Big Data Analytics by Vadlamani Ravi,Aswani Kumar Cherukuri Pdf

This comprehensive edited 2-volume handbook provides a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics. The first volume presents methodologies that support Big Data analytics, while the second volume offers a wide range of Big Data analytics applications.

Statistical Modeling in Machine Learning

Tilottama Goswami,G. R. Sinha
Statistical Modeling in Machine Learning Book PDF

Author : Tilottama Goswami,G. R. Sinha
Publisher : Academic Press
Page : 398 pages
File Size : 48,6 Mb
Release : 2022-10-29
Category : Computers
ISBN : 9780323972529

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Statistical Modeling in Machine Learning by Tilottama Goswami,G. R. Sinha Pdf

Statistical Modeling in Machine Learning: Concepts and Applications presents the basic concepts and roles of statistics, exploratory data analysis and machine learning. The various aspects of Machine Learning are discussed along with basics of statistics. Concepts are presented with simple examples and graphical representation for better understanding of techniques. This book takes a holistic approach – putting key concepts together with an in-depth treatise on multi-disciplinary applications of machine learning. New case studies and research problem statements are discussed, which will help researchers in their application areas based on the concepts of statistics and machine learning. Statistical Modeling in Machine Learning: Concepts and Applications will help statisticians, machine learning practitioners and programmers solving various tasks such as classification, regression, clustering, forecasting, recommending and more. Provides a comprehensive overview of the state-of-the-art in statistical concepts applied to Machine Learning with the help of real-life problems, applications and tutorials Presents a step-by-step approach from fundamentals to advanced techniques Includes Case Studies with both successful and unsuccessful applications of Machine Learning to understand challenges in its implementation, along with worked examples

Big Data, IoT, and Machine Learning

Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
Big Data IoT and Machine Learning Book PDF

Author : Rashmi Agrawal,Marcin Paprzycki,Neha Gupta
Publisher : CRC Press
Page : 319 pages
File Size : 54,6 Mb
Release : 2020-09-01
Category : Computers
ISBN : 9781000098280

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Big Data, IoT, and Machine Learning by Rashmi Agrawal,Marcin Paprzycki,Neha Gupta Pdf

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases

Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics

Hossain, Md Shamim,Ho, Ree Chan,Trajkovski, Goran
Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics Book PDF

Author : Hossain, Md Shamim,Ho, Ree Chan,Trajkovski, Goran
Publisher : IGI Global
Page : 445 pages
File Size : 42,9 Mb
Release : 2023-05-02
Category : Computers
ISBN : 9781668471074

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Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics by Hossain, Md Shamim,Ho, Ree Chan,Trajkovski, Goran Pdf

In the modern data-driven era, artificial intelligence (AI) and machine learning (ML) technologies that allow a computer to mimic intelligent human behavior are essential for organizations to achieve business excellence and assist organizations in extracting useful information from raw data. AI and ML have existed for decades, but in the age of big data, this sort of analysis is in higher demand than ever, especially for customer support and analytics. The Handbook of Research on AI and Machine Learning Applications in Customer Support and Analytics investigates the applications of AI and ML and how they can be implemented to enhance customer support and analytics at various levels of organizations. This book is ideal for marketing professionals, managers, business owners, researchers, practitioners, academicians, instructors, university libraries, and students, and covers topics such as artificial intelligence, machine learning, supervised learning, deep learning, customer sentiment analysis, data mining, neural networks, and business analytics.

Machine Learning for Data Science Handbook

Lior Rokach,Oded Maimon,Erez Shmueli
Machine Learning for Data Science Handbook Book PDF

Author : Lior Rokach,Oded Maimon,Erez Shmueli
Publisher : Springer Nature
Page : 975 pages
File Size : 53,5 Mb
Release : 2023-08-17
Category : Computers
ISBN : 9783031246289

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Machine Learning for Data Science Handbook by Lior Rokach,Oded Maimon,Erez Shmueli Pdf

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Big Data Analytics

Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
Big Data Analytics Book PDF

Author : Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
Publisher : Springer
Page : 276 pages
File Size : 43,7 Mb
Release : 2016-10-12
Category : Computers
ISBN : 9788132236283

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Big Data Analytics by Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao Pdf

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Big Data Analytics: Systems, Algorithms, Applications

C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Big Data Analytics Systems Algorithms Applications Book PDF

Author : C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston
Publisher : Springer Nature
Page : 412 pages
File Size : 49,8 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9789811500947

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Big Data Analytics: Systems, Algorithms, Applications by C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,Aditya Mogadala,Rohit Ghosh,L.M. Jenila Livingston Pdf

This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. In turn, the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deutsche Bank, the power provider Opower, Delta Airlines and a Chinese City Transportation application represent a valuable addition. Given its comprehensive coverage of Big Data Analytics, the book offers a unique resource for undergraduate and graduate students, researchers, educators and IT professionals alike.

Machine Learning and Big Data

Uma N. Dulhare,Khaleel Ahmad,Khairol Amali Bin Ahmad
Machine Learning and Big Data Book PDF

Author : Uma N. Dulhare,Khaleel Ahmad,Khairol Amali Bin Ahmad
Publisher : John Wiley & Sons
Page : 544 pages
File Size : 44,7 Mb
Release : 2020-09-01
Category : Computers
ISBN : 9781119654742

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Machine Learning and Big Data by Uma N. Dulhare,Khaleel Ahmad,Khairol Amali Bin Ahmad Pdf

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.