June 2025
Beginner to intermediate
38 pages
24m
Chinese
Overview
本作品已使用人工智能进行翻译。欢迎您提供反馈和意见：translation-feedback@oreilly.com
人工智能团队常常被现有工具和框架所能实现的成果所迷惑，但工具和框架并不了解你的业务。构建人工智能系统的成功关键在于报告中提到的这些几乎显而易见的策略：理解自身数据并通过有意义的指标进行衡量，分析实际的人工智能与客户互动以识别并解决真实问题，以及其他基于业务现实的务实方法。
如果你正在考虑开发人工智能产品，或者你已经面临产品表现不佳的问题，咨询顾问哈梅尔·侯赛因（Hamel Husain）的这份报告将为你提供清晰的指导，指出人工智能团队最常见的错误，并通过其客户的具体挑战及其成功解决的案例进行说明。
- 理解为何错误分析对顶级人工智能性能至关重要
- 构建值得投资的定制化界面
- 赋能非技术专家掌握人工智能技能
- 有效利用合成数据进行测试
- 了解为何人工智能产品路线图应优先考虑实验而非截止日期
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