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Frontiers In Data Science


Frontiers In Data Science
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Frontiers In Data Science


Frontiers In Data Science
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Author : Matthias Dehmer
language : en
Publisher: CRC Press
Release Date : 2017-10-16

Frontiers In Data Science written by Matthias Dehmer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Computers categories.


Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis. In fact, Big Data also belongs to this universe as it comprises data gathering, data fusion and analysis when it comes to manage big data sets. A major goal of this book is to understand data science as a new scientific discipline rather than the practical aspects of data analysis alone.



Frontiers In Statistics


Frontiers In Statistics
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Author : Jianqing Fan
language : en
Publisher: Imperial College Press
Release Date : 2006

Frontiers In Statistics written by Jianqing Fan and has been published by Imperial College Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.


During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel''s distinguished contributions.



Machine Learning And Data Mining In Materials Science


Machine Learning And Data Mining In Materials Science
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Author : Norbert Huber
language : en
Publisher: Frontiers Media SA
Release Date : 2020-04-22

Machine Learning And Data Mining In Materials Science written by Norbert Huber and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with categories.




Frontiers In Data Science


Frontiers In Data Science
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Author : Matthias Dehmer
language : en
Publisher: CRC Press
Release Date : 2017-10-16

Frontiers In Data Science written by Matthias Dehmer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Business & Economics categories.


Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis. In fact, Big Data also belongs to this universe as it comprises data gathering, data fusion and analysis when it comes to manage big data sets. A major goal of this book is to understand data science as a new scientific discipline rather than the practical aspects of data analysis alone.



Safe And Trustworthy Machine Learning


Safe And Trustworthy Machine Learning
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Author : Bhavya Kailkhura
language : en
Publisher: Frontiers Media SA
Release Date : 2021-10-29

Safe And Trustworthy Machine Learning written by Bhavya Kailkhura and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-29 with Science categories.




Big Data In Cognitive Science


Big Data In Cognitive Science
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Author : Michael N. Jones
language : en
Publisher: Psychology Press
Release Date : 2016-11-03

Big Data In Cognitive Science written by Michael N. Jones and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Computers categories.


The primary goal of this volume is to present cutting-edge examples of mining large and naturalistic datasets to discover important principles of cognition and to evaluate theories in a way that would not be possible without such scale. It explores techniques that have been underexploited by cognitive psychologists and explains how big data from numerous sources can inform researchers with different research interests and shed further light on how brain, cognition and behavior are interconnected. The book fills a major gap in the literature and has the potential to rapidly advance knowledge throughout the field. It is essential reading for any cognitive psychology researcher.



Artificial Intelligence And Big Data Analytics For Smart Healthcare


Artificial Intelligence And Big Data Analytics For Smart Healthcare
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Author : Miltiadis Lytras
language : en
Publisher: Academic Press
Release Date : 2021-10-22

Artificial Intelligence And Big Data Analytics For Smart Healthcare written by Miltiadis Lytras and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Medical categories.


Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers



Machine Learning Advanced Dynamic Omics Data Analysis For Precision Medicine


Machine Learning Advanced Dynamic Omics Data Analysis For Precision Medicine
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Author : Tao Zeng
language : en
Publisher: Frontiers Media SA
Release Date : 2020-03-30

Machine Learning Advanced Dynamic Omics Data Analysis For Precision Medicine written by Tao Zeng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-30 with categories.




Foundations Of Data Science


Foundations Of Data Science
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Author : Avrim Blum
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-23

Foundations Of Data Science written by Avrim Blum and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-23 with Computers categories.


Covers mathematical and algorithmic foundations of data science: machine learning, high-dimensional geometry, and analysis of large networks.



Frontiers In Massive Data Analysis


Frontiers In Massive Data Analysis
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2013-09-03

Frontiers In Massive Data Analysis written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-03 with Mathematics categories.


Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.