通过数据实现更好的机器学习Better Machine Learning Through Data |
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课程网址: | https://videolectures.net/videos/kdd2016_amershi_machine_learning |
主讲教师: | Saleema Amershi |
开课单位: | KDD 2016研讨会 |
开课时间: | 2025-02-04 |
课程语种: | 英语 |
中文简介: | 机器学习是算法和数据的产物。虽然机器学习研究倾向于关注算法进步,将数据视为给定,但机器学习实践却恰恰相反。从业者在使用机器学习构建预测模型方面的大部分影响力来自与数据的交互,包括精心制作用于训练的数据,并检查新数据的结果,以告知未来的迭代。在这次演讲中,我将介绍我们在微软研究院机器教学小组开发的工具和技术,以支持模型构建过程。然后,我将讨论在改进机器学习实践方面的一些开放挑战和机遇。 |
课程简介: | Machine learning is the product of both an algorithm and data. While machine learning research tends to focus on algorithmic advances, taking the data as given, machine learning practice is quite the opposite. Most of the influence practitioners have in using machine learning to build predictive models comes through interacting with data, including crafting the data used for training and examining results on new data to inform future iterations. In this talk, I will present tools and techniques we have been developing in the Machine Teaching Group at Microsoft Research to support the model building process. I will then discuss some of the open challenges and opportunities in improving the practice of machine learning. |
关 键 词: | 机器学习; 预测模型; 微软研究院 |
课程来源: | 视频讲座网 |
数据采集: | 2025-02-27:liyq |
最后编审: | 2025-02-27:liyq |
阅读次数: | 7 |