Designing Machine Learning Systems

Huyen treats machine learning as a production systems problem, covering everything around the model rather than the modelling itself. The book moves from framing a business problem as a machine learning problem and deciding whether the approach is appropriate at all, through data engineering, feature engineering and training data sampling, to model development, offline and online evaluation, and deployment. Later chapters cover data distribution shift, monitoring in production, continual learning, and the infrastructure choices sitting behind all of it. A closing chapter deals with the human side, including team structure and responsible development. Practical and specific about the failure modes that only appear once real traffic arrives.