MARC details
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03095nam a22003977a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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IIITD |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20250804163625.0 |
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250721b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780262029445 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
IIITD |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.31 |
| Item number |
KEL-F |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Kelleher, John D. |
| 245 ## - TITLE STATEMENT |
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| Title |
Fundamentals of machine learning for predictive data analytics : |
| Remainder of title |
algorithms, worked examples, and case studies |
| Statement of responsibility, etc |
by John D. Kelleher, Brian Mac Namee and Aoife D'Arcy |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication, distribution, etc |
Cambridge : |
| Name of publisher, distributor, etc |
MIT Press, |
| Date of publication, distribution, etc |
©2015 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xxii, 595 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
1. Machine learning for predictive data analytics |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
2. Data to insights to decisions |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
3. Data exploration |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
4. Information-based learning |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
5. Similarity-based learning |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
6. Probability-based learning |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
7. Error-based learning |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
8. Evaluation |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
9. Case study : customer churn |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
10. Case study : galaxy classification |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
11. The art of machine learning for predictive data analytics |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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Computers -- Artificial Intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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Data mining |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Prediction theory |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Namee, Brian Mac |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
D'Arcy, Aoife |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
