Introduction to Machine Learning:
A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learni...
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| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Saint Louis
Elsevier Science
2014
|
| Series: | Research Notes in Artificial Intelligence
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| Subjects: | |
| Online Access: | BTW01 |
| Summary: | A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginning with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog. Introduction to Machine Learning is an accessible and originalintroduction to a significant research area |
| Item Description: | Description based on publisher supplied metadata and other sources |
| Physical Description: | 1 online resource (305 pages) |
| ISBN: | 9780080509303 9781558600379 |
Staff View
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| spelling | Kodratoff, Yves Verfasser aut Introduction to Machine Learning Saint Louis Elsevier Science 2014 © 1989 1 online resource (305 pages) txt rdacontent c rdamedia cr rdacarrier Research Notes in Artificial Intelligence Description based on publisher supplied metadata and other sources A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject. Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginning with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog. Introduction to Machine Learning is an accessible and originalintroduction to a significant research area Machine learning Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 s DE-604 Erscheint auch als Druck-Ausgabe Kodratoff, Yves Introduction to Machine Learning |
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| title | Introduction to Machine Learning |
| title_auth | Introduction to Machine Learning |
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