Online Machine Learning A Practical Guide with Examples in Python /
This book deals with the exciting, seminal topic of Online Machine Learning (OML). The content is divided into three parts: the first part looks in detail at the theoretical foundations of OML, comparing it to Batch Machine Learning (BML) and discussing what criteria should be developed for a meanin...
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| Autor kompanije: | |
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| Daljnji autori: | , |
| Format: | Elektronički e-knjiga |
| Jezik: | engleski |
| Izdano: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
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| Izdanje: | 1st ed. 2024. |
| Serija: | Machine Learning: Foundations, Methodologies, and Applications,
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| Teme: | |
| Online pristup: | https://doi.org/10.1007/978-981-99-7007-0 |
| Oznake: |
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Sadržaj:
- Chapter 1:Introduction
- Chapter 2:Supervised Learning
- Chapter 3:Drift Detection and Handling
- Chapter 4:Initial Selection and Subsequent Updating of OML Models
- Chapter 5:Evaluation and Performance Measurement
- Chapter 6:Special Requirements for OML Methods
- Chapter 7:Practical Applications of Online Machine Learning
- Chapter 8:Open-Source-Software for Online Machine Learning
- Chapter 9:An Experimental Comparison of Batch and Online Machine Learning Algorithms
- Chapter 10:Hyperparameter Tuning
- Chapter 11:Summary and Outlook.