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用数据和人工智能驱动数字化转型

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用数据和人工智能驱动数字化转型

交付数据科学和机器学习产品的实用指南

Kogan Page,

15 min read
7 take-aways
Text available

What's inside?

本书贴合实际、案例详实,是不可多得的企业数字化转型指南。


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7

关键特征

  • 实用性
  • 实例
  • 内参

导读荐语

这本数字化转型指南贴合实际、案例详实,对企业人工智能和数据科学相关人员极具参考价值。其他作者主要从战略角度谈论数字化转型,但本书不同,亚历山大·博雷克(Alexander Borek)和纳丁·普里尔(Nadine Prill)更专注应用性,为中层管理者和独立工作者提供切实可行的建议。作者分享了成功数字化转型的蓝图,推荐了用来开发数字化产品的工具和编程语言,并描绘了塑造数据驱动型企业文化的过程。

浓缩书

拥抱数字化、数据决策和人工智能,否则定是死路一条。

数字化、机器学习和人工智能并非新生事物,但是,把无处不在的数据、廉价又强大的存储能力、大规模的处理能力和连接能力结合起来还是头一回出现。这种变革意味着更多人能在更多地方开发智能数字产品,从而进一步推动更多更快的颠覆性变革。

现如今,数据是企业最珍贵的资产之一,特别是独特的数据。不管处于哪个行业,企业都必须着重培养自身的数据敏感度,包括识别重要数据,收集、处理、分析此类数据,并利用这些数据获取竞争优势。也就是说,企业要雇佣数据科学、软件工程和人工智能领域的专家,还要招募端对端数字产品开发、产品生命周期管理的专业领导人才。

几乎所有企业都必须找到新的商业模型,才能应对数字科技、人工智能和机器学习给行业标准和客户需求带来的改变。虽然人工智能在特定活动(比如识别模式)中的表现优于人类,但在可预见的未来,人工智能更大的作用还是帮助人类做出更佳决策,这种效果远比人类或机器孤军作战好得多。

机器学习和人工智能持续进化。

关于作者

亚历山大·博雷克(Alexander Borek)此前是大众公司人工智能和数据分析全球负责人,现作为顾问,为企业提供数据科学和机器学习战略方面的建议。 纳丁·普里尔(Nadine Prill)在柏林触知(Taktile)公司供职,领导机器学习数字产品的开发。


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