Designing Machine Learning Systems

Author Chip Huyen, co-founder of Claypot AI, considers each design decision--such as how to process and create training data, which features to use, how often to retrain models, and what to monitor--in the context of how it can help your system as a whole achieve its objectives. The iterative framework in this book uses actual case studies backed by ample references. This book will help you tackle scenarios such as: - Engineering data and choosing the right metrics to solve a business problem - Automating the process for continually developing, evaluating, deploying, and updating models - Developing a monitoring system to quickly detect and address issues your models might encounter in production - Architecting an ML platform that serves across use cases - Developing responsible ML systems