Machine Learning and Knowledge Extraction : A Practical Guide to Turning Data into Structured Insight

Language: English

Published by Eliva Press, 2026

9999344712 / 9789999344715

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - Machine learning is often presented as a set of algorithms, while knowledge extraction is often presented as a set of information retrieval or data mining techniques. In practice, the two fields meet in operational systems that must transform records, documents, images, events, and conversations into knowledge that people can understand and use. This book treats knowledge extraction as a full process rather than a single model. The process begins with the definition of a question and ends with a maintained knowledge product: a classification, a summary, a knowledge graph, a decision rule, a searchable index, a report, or an interface used in daily work. The chapters move from conceptual foundations to project execution. They discuss data sources, representation, supervised and unsupervised learning, natural language processing, knowledge graphs, evaluation, interpretability, deployment, and governance. The approach is practical and interdisciplinary. It recognizes that technical performance is important, but that extracted knowledge must also be useful, auditable, fair, and explainable. A project that cannot be trusted or maintained cannot be considered successful, even if its model scores appear strong.…

Seller Inventory # 9789999344715

Title
Machine Learning and Knowledge Extraction : A Practical Guide to Turning Data into Structured Insight
Author
Elias Hartmann
Publisher
Eliva Press
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
9999344712
ISBN 13
9789999344715
Item weight
150 grams
Dimensions
229x152x5 mm

AHA-BUCH GmbH

Einbeck, Germany

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AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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