May 2025
Beginner to intermediate
388 pages
4h 42m
Chinese
Overview
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机器学习系统既复杂又独特。复杂是因为它们由许多不同组件构成，涉及众多利益相关者。独特是因为它们依赖数据，且数据在不同应用场景下会发生剧烈变化。本书将教你一种全面的方法，设计出可靠、可扩展、易于维护且能适应不断变化的环境和业务需求的机器学习系统。
作者Chip Huyen，Claypot AI的联合创始人，会从系统整体目标实现的角度，考量每个设计决策——例如如何处理和创建训练数据、选择哪些特征、模型需要多频繁地重新训练，以及需要监控哪些指标。本书采用的迭代框架基于实际案例研究，并辅以大量参考文献。
本书将帮助您应对以下场景：
- 工程化数据并选择合适的指标来解决业务问题
- 自动化模型持续开发、评估、部署和更新的流程
- 开发监控系统以快速检测并解决模型在生产环境中可能遇到的各类问题
- 设计适用于多种用例的机器学习平台
- 开发负责任的机器学习系统
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