导读荐语
如今,市面上出现了各种唾手可得的 AI 基础模型。它们能够应用于千行百业,出现在不计其数的场景之中。借助这些模型,即便是那些技术背景相对薄弱、甚至几乎没有 AI 经验的人,也能够打造属于自己的 AI 产品。《 AI 工程》(AI Engineering)这本书将帮助读者厘清 AI 工程与经典机器学习这两个概念的根本区别,指导大家一步步开发 AI 模型,从容应对开发过程中可能出现的各种挑战。读完本书,你将学到如何根据自身业务的特定需求来定制和改造 AI 模型,最终掌握关键方法,选择最契合的模型。记住,想要实现这一切,数据集至关重要;同样重要的是拥有一套评估方法,清晰了解项目进展情况,对 AI 工程之旅了如指掌。
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关于作者
奇普·玄(Chip Huyen),是一名作家与计算机科学家,深耕于人工智能、数据科学与叙事艺术交汇地带。她曾服务于 Snorkel AI 和英伟达(NVIDIA)。她创办了一家初创公司,专注人工智能基础设施领域。同时,她还执教斯坦福大学,教授机器学习系统设计课程。
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