Classification Big Data Analysis And Statistical Learning
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Classification Big Data Analysis And Statistical Learning
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Author : Francesco Mola
language : en
Publisher: Springer
Release Date : 2018-02-21
Classification Big Data Analysis And Statistical Learning written by Francesco Mola and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-21 with Mathematics categories.
This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.
Classification Applications With Deep Learning And Machine Learning Technologies
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Author : Laith Abualigah
language : en
Publisher: Springer Nature
Release Date : 2022-11-16
Classification Applications With Deep Learning And Machine Learning Technologies written by Laith Abualigah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-16 with Technology & Engineering categories.
This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studies’ image and data classifications. The early start-up can use it to work with product or prototype design requirement analysis and its design and development.
The 2020 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy
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Author : John MacIntyre
language : en
Publisher: Springer Nature
Release Date : 2020-11-03
The 2020 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy written by John MacIntyre and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Computers categories.
This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. 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.
Proceedings Of International Conference On Big Data Machine Learning And Applications
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Author : Ripon Patgiri
language : en
Publisher: Springer Nature
Release Date : 2021-03-22
Proceedings Of International Conference On Big Data Machine Learning And Applications written by Ripon Patgiri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-22 with Technology & Engineering categories.
This book covers selected high-quality research papers presented at the International Conference on Big Data, Machine Learning, and Applications (BigDML 2019). It focuses on both theory and applications in the broad areas of big data and machine learning. It brings together the academia, researchers, developers and practitioners from scientific organizations and industry to share and disseminate recent research findings.
Advances In Machine Learning For Big Data Analysis
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Author : Satchidananda Dehuri
language : en
Publisher: Springer Nature
Release Date : 2022-02-24
Advances In Machine Learning For Big Data Analysis written by Satchidananda Dehuri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-24 with Technology & Engineering categories.
This book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems.
Statistical Inference And Machine Learning For Big Data
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Author : Mayer Alvo
language : en
Publisher: Springer Nature
Release Date : 2022-11-30
Statistical Inference And Machine Learning For Big Data written by Mayer Alvo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-30 with Mathematics categories.
This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems. The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented. This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.
Intelligence Science And Big Data Engineering Big Data And Machine Learning
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Author : Zhen Cui
language : en
Publisher: Springer Nature
Release Date : 2019-11-28
Intelligence Science And Big Data Engineering Big Data And Machine Learning written by Zhen Cui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Computers categories.
The two volumes LNCS 11935 and 11936 constitute the proceedings of the 9th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2019, held in Nanjing, China, in October 2019. The 84 full papers presented were carefully reviewed and selected from 252 submissions.The papers are organized in two parts: visual data engineering; and big data and machine learning. They cover a large range of topics including information theoretic and Bayesian approaches, probabilistic graphical models, big data analysis, neural networks and neuro-informatics, bioinformatics, computational biology and brain-computer interfaces, as well as advances in fundamental pattern recognition techniques relevant to image processing, computer vision and machine learning.
Demystifying Big Data Machine Learning And Deep Learning For Healthcare Analytics
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Author : Pradeep N
language : en
Publisher: Academic Press
Release Date : 2021-06-10
Demystifying Big Data Machine Learning And Deep Learning For Healthcare Analytics written by Pradeep N and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-10 with Science categories.
Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. - Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies - Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics - Unique case study approach provides readers with insights for practical clinical implementation
Statistical Learning Of Complex Data
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Author : Francesca Greselin
language : en
Publisher: Springer Nature
Release Date : 2019-09-06
Statistical Learning Of Complex Data written by Francesca Greselin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-06 with Mathematics categories.
This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification. It gathers selected and peer-reviewed contributions presented at the 11th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), held in Milan, Italy, on September 13–15, 2017.
Big Data Machine Learning And Data Mining Explained
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Author : Chitrali Kaul
language : en
Publisher: Educohack Press
Release Date : 2025-02-28
Big Data Machine Learning And Data Mining Explained written by Chitrali Kaul and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-28 with Computers categories.
Big Data, Machine Learning, and Data Mining Explained is an essential guide for understanding the world of big data, data mining, and machine learning. This book is perfect for students, professionals, and anyone eager to learn about these rapidly evolving technologies and their profound impact on our world. We provide comprehensive explanations of big data, data mining, and machine learning, making complex algorithms and models easy to understand. This book covers all key terms and processes, offering insights into how these technologies are transforming industries and markets. You'll also gain a glimpse into the future and understand the career opportunities in these fields. We delve into how big data is revolutionizing business practices, enhancing growth, and improving customer reach. Data mining techniques are explained in detail, showcasing how they help in decision-making and predicting trends. Furthermore, we explore machine learning, a branch of artificial intelligence, highlighting its role in processing data through advanced models and algorithms. Designed to be accessible and informative, Big Data, Machine Learning, and Data Mining Explained will help you navigate and thrive in this world of emerging technologies.