Machine learning / Tom M. Mitchell, Carnegie Mellon University.
Material type:
TextLanguage: English Series: McGraw-Hill series in computer scienceNew York : McGraw-Hill, [1997]©1997 Description: xvii, 414 pages : illustrations ; 25 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9780071154673 (paperback)Subject(s): Machine learning | Computer algorithmsLOC classification: Q325.5 .M58 1997| Item type | Current library | Shelving location | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
| Books | MEF Üniversitesi Kütüphanesi | Genel Koleksiyon | Q 325.5 .M58 1997 (Browse shelf (Opens below)) | Available | 0011385 |
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| Q 325.5 .A47 2014 Introduction to machine learning / | Q 325.5 .G66 2017 Deep learning / | Q 325.5 .H39 2009 The elements of statistical learning : data mining, inference, and prediction / | Q 325.5 .M58 1997 Machine learning / | Q 325.5 .M87 2012 Machine learning : a probabilistic perspective / | Q 325.6 .R45 2018 Reinforcement learning : an introduction / | Q 327 .B57 2006 Pattern recognition and machine learning / |
Includes bibliographical references and indexes.
1. Introduction -- 2. Concept Learning and the General-to- Specific Ordering -- 3. Decision Tree Learning -- 4. Artificial Neural Networks -- 5. Evaluating Hypotheses -- 6. Bayesian Learning -- 7. Computational Learning Theory - - 8. Instance-Based Learning -- 9. Genetic Algorithms -- 10. Learning Sets of Rules -- 11. Analytical Learning -- 12. Combining Inductive and Analytical Learning -- 13. Reinforcement Learning
Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automatically improve through experience and that automatically infer general laws from specific data