New MEAP! In real-time uses, data changes fast and traditional batch machine learning models struggle. They become stale as soon as they’re deployed—and bringing them up to date means expensive and time consuming retraining. This book reveals how to build models that learn in production. You’ll learn to use event-driven methodologies for real-time data processing, and integrate online machine learning models into real-time data pipelines for responsive and adaptive applications.

Plus, the same offer also applies to Causal AI, Machine Learning Algorithms in Depth, Automated Machine Learning in Action, and ML.NET for Machine Learning and Generative AI.