Machine learning / Tom M. Mitchell
Dil: İngilizce Seri kaydı: McGraw-Hill series in computer scienceYayıncı: New York: The McGraw-Hill, 1997,©1997Telif hakkı tarihi:©1997Tanım: xvii,431 pagess : illustrations ; 25 cmİçerik türü:- text
- unmediated
- volume
- 0070428077
- Q325.5 .M58 1997
İçindekiler:
Özet: 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
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
| Materyal türü | Ana kütüphane | Koleksiyon | Yer numarası | Durum | İade tarihi | Barkod | Materyal Ayırtmaları | |
|---|---|---|---|---|---|---|---|---|
Kitap
|
Mehmet Akif Ersoy Merkez Kütüphanesi Genel Koleksiyon | Non-fiction | Q325.5 .M58 1997 (Rafa gözat(Aşağıda açılır)) | Kullanılabilir | 015059 |
Toplam ayırtılanlar: 0
Includes bibliographical references and index.
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
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