Appendix
Machine Learning Pipeline in Production
In this appendix, we will look at when and at which step we incorporate the data imbalance-handling techniques within a production machine learning pipeline. This mainly applies to supervised classification problems.
Machine learning training pipeline
A machine learning pipeline is the end-to-end process of training one or more machine learning models and then deploying them to a live environment. It may involve stages such as data collection, model training, validation, deployment, monitoring, and iterative improvement, with a focus on scalability, efficiency, and robustness.
Various steps during the offline training are shown in Figure A.1. Please note that some of the steps may not be necessary ...
Get Machine Learning for Imbalanced Data now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
