Design Automobile Learning Systems: An Iterative Procedure For Production-Ready Applications
Machine learning systems are both complex as well as unique. Complex because they consist of many dissimilar components as well as take many dissimilar stakeholders. Unique because they're information dependent, amongst information varying wildly from ane role case to the side by side. In this volume, yous'll acquire a holistic approach to design ML systems that are reliable, scalable, maintainable, in addition to adaptive to changing environments as well as business organization requirements.
Author Chip Huyen, co-founder of Claypot AI, considers each pattern conclusion--such as how to procedure as well as make preparation data, which features to purpose, how frequently to retrain models, and what to monitor--inwards the context of how it can assistance your organization equally a whole achieve its objectives. The iterative framework inwards this book uses actual instance studies backed by ample references.
This volume volition assist yous tackle scenarios such every bit:
- Engineering information and choosing the right metrics to solve a business problem
- Automating the process for continually developing, evaluating, deploying, in addition to updating models
- Developing a monitoring organization to rapidly find and address issues your models might encounter in product
- Architecting an ML platform that serves across purpose cases
- Developing responsible ML systems
