2021年1月吃：慢烤手撕猪肉和椒麻鸡
26 Jan 2021记录且分享1月享受的两道菜。
A comprehensive guide to the EM algorithm with intuitions, examples, Python implementation, and maths
By now, you’ve probably seen a few, if not many, articles on how deep learning could help detect COVID-19. In particular, convolutional neural networks (CNNs) have been studied as a faster and cheaper alternative to the gold-standard PCR test by just analyzing the patient’s computed tomography (CT) scan. It’s not surprising since CNN is excellent at image recognition; many places have CT scanners rather than COVID-19 testing kits (at least initially).
I am not a deep learning researcher, but I’ve come to know a few things about neural networks through various exposures. I’ve always heard that CNN is a type of neural network that’s particularly good at image-related problems. But, what does that really mean? What’s with the word “convolutional”? What’s so unusual about an image-related problem that a different network is required?
This is a collection of my notes on various topics of statistical learning. It is intended as a knowledge repository for some of the unexpected discoveries, less-talked-about connections, and under-the-hood concepts for statistical learning. It’s a work in progress that I will periodically update.
时间是个奇妙的东西。第一次知道《菊与刀》还是在中学的课堂上，这书可能是推荐课外阅读丛书之一，那时的我对日本没什么特别兴趣，只依稀记得徐慧老师在讲台上介绍这本书的模样。十年之后，偶然再次看到此书，对樱花之国的历史和文化有了一定了解，读罢，感触颇多。
五月因为疫情的原因继续在家里工作。这段时间工作重心主要在写东西上面，不太需要跑大量的数据、也不需要太多跟同事老板的交流，虽然我蛮想念办公室的espresso咖啡和时不时不同领域的人过来做的seminar的，这两件事儿家里没法复制。
周末读Aeon的一篇文章：Algorithms associating appearance and criminality have a dark past，讲现在有研究人员用机器学习算法通过人脸来判断某人犯罪的几率。文中讲到这种从人外表提取预见性特征的尝试，在犯罪学历史上并不新奇，19世纪的意大利犯罪学家Cesare Lombroso认为罪犯的脸部有独特的样貌：突出的前额、鹰型鼻梁；而18世纪的Francis Galton则尝试回答一个更广泛的问题：人的外表跟他或她的健康状况、犯罪倾向、智力等等有关系吗？或者说，人的基因是否决定了健康、行为、智力和竞争力？