Synthesized answer
The central thesis of this text is to teach a holistic approach to designing machine learning systems that are reliable, scalable, maintainable, and adaptive [4]. It emphasizes considering each design decision within the context of how it helps the system as a whole achieve its objectives [4].
The book aims to help readers tackle various scenarios, including engineering data, choosing metrics, automating the model development and deployment process, developing monitoring systems, architecting ML platforms, and developing responsible ML systems [1, 2]. It uses an iterative framework with case studies and references to achieve this [1, 4].
Synthesized from the book passages below. Chat with the book on Feynman for follow-up.
From the book
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
Categories: Computers Pages: 388 Snippet: 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 ...
Title: Designing Machine Learning Systems by Chip Huyen
Description: Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. 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…