Online Machine Learning: A Practical Guide with Examples in Python (Hardcover, 2024)

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.