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Designing Machine Learning Systems
Chip Huyen你有多喜歡這本書?
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Many tutorials show you how to develop ML systems from ideation to deployed models. But with constant changes in tooling, those systems can quickly become outdated. Without an intentional design to hold the components together, these systems will become a technical liability, prone to errors and be quick to fall apart. In this book, Chip Huyen provides a framework for designing real-world ML systems that are quick to deploy, reliable, scalable, and iterative. These systems have the capacity to learn from new data, improve on past mistakes, and adapt to changing requirements and environments. You'll learn everything from project scoping, data management, model development, deployment, and infrastructure to team structure and business analysis. Learn the challenges and requirements of an ML system in production Build training data with different sampling and labeling methods Leverage best techniques to engineer features for your ML models to avoid data leakage Select, develop, debug, and evaluate ML models that are best suit for your tasks Deploy different types of ML systems for different hardware Explore major infrastructural choices and hardware designs Understand the human side of ML, including integrating ML into business, user experience, and team structure
年:
2022
版本:
1
出版商:
O'Reilly Media
語言:
english
頁數:
389
ISBN 10:
1098107969
ISBN 13:
9781098107963
文件:
PDF, 15.49 MB
你的標籤:
IPFS:
CID , CID Blake2b
english, 2022
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