O'Reilly、Cloudera 主办
Make Data Work
2016年8月3-4日:培训
2016年8月4-6日:会议
北京,中国

商业应用中的数据科学和机器学习

09:00–12:30 2016年8月04日
数据科学与高级分析
地点: 多功能厅5B+C(Function Room 5B+C)

必要预备知识

参与者并不需要具有丰富的机器学习的知识。

描述

数据科学不仅关于机器学习和复杂的算法的应用,更重要是实现商业价值。因此,它最本质的原则就是理解业务需求,进而形成可行的机器学习算法和与之配套的工程方案。本课程会向你介绍与专家和管理人员对话所需的基础技术知识、语言与框架。

课程组织

本课程从实践角度出发,结合了复杂的算法、工程技能以及商业案例。
第一部分:数据科学的工程框架
第二部分:机器学习领域鸟瞰。机器学习的基础知识,以及最新技术的潜力和局限。
第三部分:案例研究。从三个案例来介绍了机器学习技术和应用。每个案例都由下面几部分组成:

  • 业务背景
  • 从数据中提取机器学习问题
  • 选择合适的算法和技术
  • 了解、理解和传达分析的结果
  • 由算法到生产系统的实现
Photo of Angie Ma

Angie Ma

Faculty

Angie Ma is co-founder and COO of Faculty, a London-based AI tech startup that provides strategy, software and skills. Faculty has delivered more than 300 commercial data science projects across 23 sectors and 8 countries. Angie is passionate about real-world applications of machine learning that generate business value for companies and organizations and has experience delivering complex projects from prototyping to implementation. A physicist by training, Angie was previously a researcher in nanotechnology working on developing optical detection for medical diagnostics.

Photo of Yingsong Zhang

Yingsong Zhang

ASI Data Science

Yingsong Zhang is a data scientist at ASI, where she has worked on everything from social media data to special data from clients to build predictive models. Yingsong has published over 10 first-author research papers in top journals and conferences in the field of signal/image processing and has accumulated extensive experience in algorithm design and information representation. She recently completed a three-year postdoc project at Imperial College London developing sampling theory and the application system. Yingsong holds a BA in mathematics, an MSc in artificial intelligence and pattern recognition from one of China’s top universities, and a PhD in signal and image processing from Cambridge University.

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