Online Machine Learning (Record no. 87461)

000 -LEADER
fixed length control field 03994nam a22005415i 4500
001 - CONTROL NUMBER
control field 978-981-99-7007-0
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730171227.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240205s2024 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789819970070
-- 978-981-99-7007-0
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
245 10 - TITLE STATEMENT
Title Online Machine Learning
Sub Title A Practical Guide with Examples in Python /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 155 p. 49 illus., 38 illus. in color.
490 1# - SERIES STATEMENT
Series statement Machine Learning: Foundations, Methodologies, and Applications,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Chapter 1:Introduction -- Chapter 2:Supervised Learning -- Chapter 3:Drift Detection and Handling -- Chapter 4:Initial Selection and Subsequent Updating of OML Models -- Chapter 5:Evaluation and Performance Measurement -- Chapter 6:Special Requirements for OML Methods -- Chapter 7:Practical Applications of Online Machine Learning -- Chapter 8:Open-Source-Software for Online Machine Learning -- Chapter 9:An Experimental Comparison of Batch and Online Machine Learning Algorithms -- Chapter 10:Hyperparameter Tuning -- Chapter 11:Summary and Outlook.
520 ## - SUMMARY, ETC.
Summary, etc This book deals with the exciting, seminal topic of Online Machine Learning (OML). The content is divided into three parts: the first part looks in detail at the theoretical foundations of OML, comparing it to Batch Machine Learning (BML) and discussing what criteria should be developed for a meaningful comparison. The second part provides practical considerations, and the third part substantiates them with concrete practical applications. The book is equally suitable as a reference manual for experts dealing with OML, as a textbook for beginners who want to deal with OML, and as a scientific publication for scientists dealing with OML since it reflects the latest state of research. But it can also serve as quasi OML consulting since decision-makers and practitioners can use the explanations to tailor OML to their needs and use it for their application and ask whether the benefits of OML might outweigh the costs. OML will soon become practical; it is worthwhile to get involved with it now. This book already presents some tools that will facilitate the practice of OML in the future. A promising breakthrough is expected because practice shows that due to the large amounts of data that accumulate, the previous BML is no longer sufficient. OML is the solution to evaluate and process data streams in real-time and deliver results that are relevant for practice.
700 1# - AUTHOR 2
Author 2 Bartz, Eva.
700 1# - AUTHOR 2
Author 2 Bartz-Beielstein, Thomas.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-99-7007-0
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2024.
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-- computer
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-- rdamedia
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-- online resource
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347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine learning.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Machine Learning.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2730-9916
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