Ali Rahimi's talk at NIPS(NIPS 2017 Test-of-time award presentation)

推荐理由

For a more cutting and insightful critique, watch Ali Rahimi's short talk at NIPS 2017

强烈推荐ssivark · 原文2018年2月

说明

这是2017年由ObservantVids发布的一部演讲，主题归在Machine learning & deep learning。它讲的是rigor in machine learning这一支里的具体问题，而不是把整个领域扫一遍。适合已经能看懂基本术语、想继续往下走的人。内容上可以概括成：Ali Rahimi's NIPS 2017 Test-of-Time award talk, in which he argues that modern machine learning has become alchemy, working without being rigorously understood. He calls for more rigor and understanding in the field.这些读者给出的理由，核心是：HN points to it as the sharpest, most-quoted critique of deep learning practice, and cites it whenever ML reliability or understanding is debated.讲法不绑某一条新闻，过几年仍然可以当材料看。从2018年到2025年，有3位不同的读者在3个不同月份把它推荐出来，其中明确叫别人去看的有2次。适合一次性看完。讲者把一个判断讲透，演示是在给这个判断配例子。如果已经会了基本定义，就把注意力放在它怎么把rigor in machine learning变成能跟着复述的例子。

视频信息

频道

ObservantVids

时长

23 分 20 秒

发布年份

2017

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