Encyclopedia Of Machine Learning And Data Mining
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Encyclopedia Of Machine Learning And Data Mining
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Author : Claude Sammut
language : en
Publisher: Springer
Release Date : 2017-03-15
Encyclopedia Of Machine Learning And Data Mining written by Claude Sammut and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-15 with Computers categories.
This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable literature references, providing the reader with a portal to more detailed information on any given topic.Topics for the Encyclopedia of Machine Learning and Data Mining include Learning and Logic, Data Mining, Applications, Text Mining, Statistical Learning, Reinforcement Learning, Pattern Mining, Graph Mining, Relational Mining, Evolutionary Computation, Information Theory, Behavior Cloning, and many others. Topics were selected by a distinguished international advisory board. Each peer-reviewed, highly-structured entry includes a definition, key words, an illustration, applications, a bibliography, and links to related literature.The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals who employ machine learning and data mining methods in their projects. Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to vital information on the topic.
Encyclopedia Of Machine Learning
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Author : Claude Sammut
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-28
Encyclopedia Of Machine Learning written by Claude Sammut and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-28 with Computers categories.
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Encyclopedia Of Data Science And Machine Learning
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2023-01-20
Encyclopedia Of Data Science And Machine Learning written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Encyclopedia Of Machine Learning And Data Mining
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Author : Claude Sammut
language : en
Publisher:
Release Date :
Encyclopedia Of Machine Learning And Data Mining written by Claude Sammut and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Machine learning categories.
Encyclopedia Of Data Warehousing And Mining Second Edition
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2008-08-31
Encyclopedia Of Data Warehousing And Mining Second Edition written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-31 with Computers categories.
There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.
Encyclopedia Of Data Science And Machine Learning Vol 1
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Author : John Wang
language : en
Publisher: Encyclopedia of Data Science and Machine Learning
Release Date : 2022-10-14
Encyclopedia Of Data Science And Machine Learning Vol 1 written by John Wang and has been published by Encyclopedia of Data Science and Machine Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-14 with categories.
Encyclopedia Of Machine Learning
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Author : Claude Sammut
language : en
Publisher: Springer
Release Date : 2010-11-12
Encyclopedia Of Machine Learning written by Claude Sammut and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-12 with Computers categories.
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Machine Learning And Data Mining
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Author : Igor Kononenko
language : en
Publisher: Elsevier
Release Date : 2007-04-30
Machine Learning And Data Mining written by Igor Kononenko and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-04-30 with Computers categories.
Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions
Encyclopedia Of Data Warehousing And Mining
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Author : John Wang
language : en
Publisher: IGI Global Snippet
Release Date : 2009
Encyclopedia Of Data Warehousing And Mining written by John Wang and has been published by IGI Global Snippet this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Business & Economics categories.
"This set offers thorough examination of the issues of importance in the rapidly changing field of data warehousing and mining"--Provided by publisher.
Introduction To Algorithms For Data Mining And Machine Learning
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Author : Xin-She Yang
language : en
Publisher: Academic Press
Release Date : 2019-07-15
Introduction To Algorithms For Data Mining And Machine Learning written by Xin-She Yang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-15 with Mathematics categories.
Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages