An Elevator Pitch on Deep Learning

Yuan-Ting Hu, A. Schwing
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Abstract

Machine learning improves all aspects of our life and very few days pass where we don't interact with a machine learning driven application. For example, we may use fitness trackers that monitor the quality of our sleep. Before leaving to work, we may check the weather forecast. To get to work, we use a navigation system that predicts the fastest route to our first meeting. On the road, we use voice commands to interact with our phone. Web searches and e-commerce recommendations are based on machine learning. Cameras detect faces when we take a picture and our email inboxes are protected by spam filters, which are designed using machine learning tools.
关于深度学习的电梯演讲
机器学习改善了我们生活的方方面面,我们几乎每天都在使用机器学习驱动的应用程序。例如,我们可以使用健康追踪器来监控我们的睡眠质量。在上班之前,我们可以看看天气预报。为了上班,我们使用导航系统来预测到达第一次会议的最快路线。在路上,我们使用语音命令与手机互动。网络搜索和电子商务推荐都是基于机器学习。当我们拍照时,摄像头会检测人脸,我们的电子邮件收件箱受到垃圾邮件过滤器的保护,这些过滤器是用机器学习工具设计的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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