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AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS
Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author--an expert in the field--presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection--essential elements of most applied projects. This important resource:
- Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods
- Presents R source code which shows how to apply and interpret many of the techniques covered
- Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions
- Contains useful information for effectively communicating with clients
A volume in the popular Wiley Series in Probability and Statistics, Machine Learning a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning.
AN INTRODUCTION TO MACHINE LEARNING THAT INCLUDES THE FUNDAMENTAL TECHNIQUES, METHODS, AND APPLICATIONS
Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concepts, approaches, and applications of machine learning. The author--an expert in the field--presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. The design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods. Understanding these principles leads to more flexible and successful applications. Machine Learning: a Concise Introduction also includes methods for optimization, risk estimation, and model selection--essential elements of most applied projects. This important resource:
- Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods
- Presents R source code which shows how to apply and interpret many of the techniques covered
- Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions
- Contains useful information for effectively communicating with clients
A volume in the popular Wiley Series in Probability and Statistics, Machine Learning a Concise Introduction offers the practical information needed for an understanding of the methods and application of machine learning.
| Erscheinungsjahr: | 2018 |
|---|---|
| Genre: | Importe |
| Medium: | Buch |
| Reihe: | Wiley Series in Probability and Statistics|Wiley Probability and Statisti |
| Inhalt: | Gebunden |
| ISBN-13: | 9781119439196 |
| ISBN-10: | 1119439191 |
| Einband: | Gebunden |
| Autor: | Knox, Steven W. |
| Hersteller: | WILEY |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 236 x 154 x 25 mm |
| Von/Mit: | Steven W. Knox |
| Erscheinungsdatum: | 13.07.2018 |
| Gewicht: | 0,703 kg |
| Erscheinungsjahr: | 2018 |
|---|---|
| Genre: | Importe |
| Medium: | Buch |
| Reihe: | Wiley Series in Probability and Statistics|Wiley Probability and Statisti |
| Inhalt: | Gebunden |
| ISBN-13: | 9781119439196 |
| ISBN-10: | 1119439191 |
| Einband: | Gebunden |
| Autor: | Knox, Steven W. |
| Hersteller: | WILEY |
| Verantwortliche Person für die EU: | preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 236 x 154 x 25 mm |
| Von/Mit: | Steven W. Knox |
| Erscheinungsdatum: | 13.07.2018 |
| Gewicht: | 0,703 kg |
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