技术
- 分析与建模 - 机器学习
- 传感器 - 液体检测传感器
适用行业
- 教育
- 金融与保险
适用功能
- 产品研发
- 质量保证
用例
- 对话机器人
- 机器翻译
服务
- 数据科学服务
- 培训
关于客户
该客户是一家全球咨询公司,属于“四大”之一,拥有 170 多年的历史。该公司的声誉建立在严格的分析和预测变化的能力之上。它致力于为其多元化的专家团队提供最新、相关的会计、审计和行业信息。该公司拥有遍布 150 个国家/地区的超过 300,000 名专家,他们每天花费数小时手动审查各种会计、审计和行业信息。该公司数据科学团队的任务是利用人工智能/机器学习来减少这种成本高昂的工作,并通过帮助确定哪些客户最有可能接受审计来进行创新。
挑战
一家拥有百年历史的全球知名咨询公司正在寻求利用人工智能来增强其审计能力。该公司的声誉取决于其进行彻底审计的能力,无论审计规模、复杂程度或地点如何。该公司的专家花费大量时间手动审查各种会计、审计和行业信息,这一过程既耗时又昂贵。该公司估计每次审计员搜寻持续 10 分钟,平均花费 50-60 美元。该公司数据科学团队的任务是简化新闻监控,以预测资本市场、监管趋势或技术创新的变化。他们的目标是使用自定义 NLP 模型自动分析、分类和从各种来源提取关键客户信息。然而,他们在标记机器学习算法的训练数据方面面临挑战。三位专家每周需要标记 500 个训练数据点,他们发现几乎不可能动态适应数据或业务目标的变化。
解决方案
该公司与 Snorkel AI 合作构建了一个 NLP 应用程序,可以对新闻文章是否与原始搜索词相关进行分类。 Snorkel Flow 的程序化标记功能使团队能够在短短几个小时内标记 10,000 多篇新闻文章,而这项任务需要人工审核团队花费近一年的时间。使用 Snorkel Flow 标记的数据比之前的手工标记方法准确 32%。该团队还使用 Snorkel Flow 的引导误差分析来快速提高模型质量并推动细粒度修正,在短短几天内将他们的 F1 分数从 70 提高到 85。 Snorkel Flow 还使团队能够通过调整标签功能而不是手动重新标签来快速应对不断变化的市场条件和业务需求。使用 Snorkel Flow 的注释器套件显着改善了中小企业和数据科学家之间的协作。
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