| ISBN |
9783031394775 |
| 기타 표준번호 |
10.1007/978-3-031-39477-5 |
| 청구기호 |
Q336 |
| 형태사항 |
XXII, 267 p. 50 illus., 33 illus. in color. online resource.
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| 언어 |
English |
| 내용 |
Preface -- 1 Introduction -- 2 The Automated Scientific Process -- 3 The (Black Box) Machine Learning Process -- 4 Information Theory -- 5 Capacity -- 6 The Mechanics of Generalization -- 7 Meta-Math: Exploring the Limits of Modeling -- 8 Capacity of Neural Networks -- 8 Capacity of Neural Networks -- 10 Capacities of some other Machine Learning Methods -- 11 Data Collection and Preparation -- 12 Measuring Data Sufficiency -- 13 Machine Learning Operations -- 14 Explainability -- 15 Repeatability and Reproducibility -- 16 The Curse of Training and the Blessing of High Dimensionality -- 16 The Curse of Training and the Blessing of High Dimensionality -- Appendix A Recap: The Logarithm -- Appendix B More on Complexity -- Appendix C Concepts Cheat Sheet -- Appendix D A Review Form that Promotes Reproducibility -- List of Illustrations -- Bibliography.
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| 주제 |
Artificial intelligence --Data processing.
Machine learning.
Data structures (Computer science).
Information theory.
Expert systems (Computer science).
Artificial intelligence.
Data Science.
Machine Learning.
Data Structures and Information Theory.
Knowledge Based Systems.
Artificial Intelligence.
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| 보유판 및 특별호 저록 |
Springer Nature eBook
Printed edition: 9783031394768
Printed edition: 9783031394782
Printed edition: 9783031394799
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| QR CODE |
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