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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Etat : New. Print on Demand. This book explores the performance of concurrency control mechanisms in multi-user database systems â" mechanisms responsible for maintaining data integrity and ensuring a consistent view for each user. Despite significant mathematical foundations in the field, quantitative performance evaluation remains in its early stages. This book proposes a methodology for analyzing the performance of these mechanisms, based on the paradigms of physical sciences. The author presents a controlled experiments approach, leading to hypotheses about system behavior. This paves the way for model propositions that aim to explain experimental data. The proposed models are rigorously tested by comparing their predicted results to results of new experiments. The author employs this methodology to dynamic two-phase locking (2PL), one of the fundamental techniques for database concurrency control. Through detailed simulation programs, the author uncovers interesting behavior, such as the logarithmic increase of the mean deadlock rate with the ratio of transactions in the system divided by the total number of database items. The book introduces a model to explain the experimental results, using the theory of the occupancy problems and Markov processes. The model captures the basic trends of system behavior with high accuracy. It also compares and tests several variations of dynamic 2PL. The insights provided by this book will be of great value to researchers and practitioners working in the field of database systems, particularly those interested in concurrency control mechanisms and performance analysis. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item.…

Etat : New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Etat : Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Etat : New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Etat : New. 3rd Edition.

Etat : New.

Etat : Hervorragend. Zustand: Hervorragend | Seiten: 996 | Sprache: Englisch | Produktart: Bücher | This book is a major update to the very successful first and second editions (2005 and 2010) of Data Mining and Knowledge Discovery Handbook. Since the last edition, this field has continued to evolve and to gain popularity. Existing methods are constantly being improved and new methods, applications and aspects are introduced. The new title of this handbook and its content reflect these changes thoroughly. Some existing chapters have been brought up to date. In addition to major revision of the existing chapters, the new edition includes totally new topics, such as: deep learning, explainable AI, human factors and social issues and advanced methods for big-data. The significant enhancement to the content reflects the growth in importance of data science. The third edition is also a timely opportunity to incorporate many other changes based on peers and students¿ feedback.This comprehensive handbook also presents a coherent and unified repository of data science major concepts, theories, methods, trends, challenges and applications. It covers all the crucial important machine learning methods used in data science.Today's accessibility and abundance of data make data science matters of considerable importance and necessity. Given the field's recent growth, it's not surprising that researchers and practitioners now have a wide range of methods and tools at their disposal. While statistics is fundamental for data science, methods originated from artificial intelligence, particularly machine learning, are also playing a significant role.This handbook aims to serve as the main reference for researchers in the fields of information technology, e-Commerce, information retrieval, data science, machine learning, data mining, databases and statistics as well as advanced level students studying computer science or electrical engineering. Practitioners working within these related fields and data scientists will also want to purchase this handbook as a reference.…

Etat : New.

Etat : New.

Etat : New.

Etat : New.

Etat : New. In English.

Taschenbuch. Etat : Neu. Machine Learning for Data Science Handbook | Data Mining and Knowledge Discovery Handbook | Lior Rokach (u. a.) | Taschenbuch | vii | Englisch | 2024 | Springer | EAN 9783031246302 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : As New. Unread book in perfect condition.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a major update to the very successful first and second editions (2005 and 2010) of Data Mining and Knowledge Discovery Handbook. Since the last edition, this field has continued to evolve and to gain popularity. Existing methods are constantly being improved and new methods, applications and aspects are introduced. The new title of this handbook and its content reflect these changes thoroughly. Some existing chapters have been brought up to date. In addition to major revision of the existing chapters, the new edition includes totally new topics, such as: deep learning, explainable AI, human factors and social issues and advanced methods for big-data. The significant enhancement to the content reflects the growth in importance of data science. The third edition is also a timely opportunity to incorporate many other changes based on peers and students' feedback.This comprehensive handbook also presents a coherent and unified repository of data science major concepts, theories, methods, trends, challenges and applications. It covers all the crucial important machine learning methods used in data science.Today's accessibility and abundance of data make data science matters of considerable importance and necessity. Given the field's recent growth, it's not surprising that researchers and practitioners now have a wide range of methods and tools at their disposal. While statistics is fundamental for data science, methods originated from artificial intelligence, particularly machine learning, are also playing a significant role.This handbook aims to serve as the main reference for researchersin the fields of information technology, e-Commerce, information retrieval, data science, machine learning, data mining, databases and statistics as well as advanced level students studying computer science or electrical engineering.Practitioners working within these related fields and data scientists will also want to purchase this handbook as a reference. …

Hardcover. Etat : Brand New. 3rd edition. 992 pages. 9.25x6.10x2.40 inches. In Stock.

Softcover. Etat : gut. 2024. Machine Learning for Data Science Handbook In deutscher Sprache. pages.

Etat : new. Questo è un articolo print on demand.

Etat : new. Questo è un articolo print on demand.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.