The Book of Why 2025 pdf epub mobi 电子书

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The Book of Why 2025 pdf epub mobi 电子书著者简介

Judea Pearl is a professor of computer science at UCLA and winner of the 2011 Turing Award and the author of three classic technical books on causality. He lives in Los Angeles, California.

Dana Mackenzie is an award-winning science writer and the author of The Big Splat, or How Our Moon Came to Be. He lives in Santa Cruz, California.

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发表于2025-03-03

The Book of Why 2025 pdf epub mobi 电子书

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“20世纪50年代末60年代初,统计学家和医生就整个20世纪最引人注目的一个医学问题产生了意见冲突:吸烟会导致肺癌吗?在这场辩论过去了半个世纪之后的现在,我们认为答案是理所当然的。但在当时,这个问题完全处于迷雾之中。” 01 — 书比较厚，正文346页，注释26页。内容也相对硬核...

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作为一名学习经管类专业的学生，这本书给了我许多更深入的思考。作者作为人工智能领域的专家，对于因果关系的理解鞭辟入里，使人茅塞顿开。例如开篇提及，在统计学课程上，学生们经常被教导“相关性不代表因果”，但往往很多的教导都止步于此——学生们知道了什么不是因果，却...

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出版者:Allen Lane

作者:Judea Pearl

出品人:

页数:400

译者:

出版时间:2018-5-15

价格:GBP 25.00

装帧:Hardcover

isbn号码:9780241242636

丛书系列:

图书标签: 人工智能统计学因果論 Causality 计算机 Statistics AI 思维

The Book of Why 2025 pdf epub mobi 电子书图书描述

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence

"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality--the study of cause and effect--on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

The Book of Why 2025 pdf epub mobi 电子书

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Rubin在课上还喷了Judea一顿，表示看不惯这种拿概率图建模的方法。。不过do calculus如何只从数据中得到因果关系确实有趣。关于因果推断的模型到底哪个才是有用的，见仁见智吧

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老爷子对概率和因果的区别还很有洞见的

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科学法是贝叶斯定理的一次应用。因果图形式化因果结构，do算子对有向无环图中指向X的有向边全部切断。由于变量不能全部观测，用前门准则来控制无法观察到的混杂因素，与RCT目标一致；若变量集合Z相对于（X,Y）满足后门准则，则X到Y因果可识别。感觉这些都是对相关性不能解决以及解决起来复杂的问题透明优化。反事实算法则扩宽数据解答问题的范围，NIE形式化间接影响。结构因果模型很大的一个优点就是对于线性非线性函数、离散或连续变量都有效。作者太卖关子，前几章讲统计学史，旧故事很多，7-9章是干货。思路是经典宏观实践的，因果哲学讲得很浅。但是应用领域极为广泛，毕竟是对相关性大改良，文科也能用呐。不知道因果模型处理相互干涉和叠加态什么的会怎么样。可能要读Causality一书才能深刻了解本书数学化的严格证明。

The Book of Why 2025 pdf epub mobi 电子书