The Book of Why pdf epub mobi txt 电子书下载 2025

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Judea Pearl

Basic Books

2018-5-15

432

USD 32.00

Hardcover

9780465097609

图书标签: 统计逻辑方法论计算机因果哲学科普 AI

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发表于2025-02-27

The Book of Why epub 下载 mobi 下载 pdf 下载 txt 电子书下载 2025

The Book of Why pdf epub mobi txt 电子书下载 2025

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 下载 mobi epub pdf txt 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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The Book of Why pdf epub mobi txt 电子书下载

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购买链接：https://item.taobao.com/item.htm?spm=a1z38n.10677092.0.0.2fd21debCjUKdJ&id=574000401704

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老爷爷的书刷第二遍了，怀着无比崇敬的心情。我想我的新年愿望就是把这书再刷几遍，然后争取看懂老爷爷的其他书

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Heckman, Rubin, Pearl的爱恨情仇啊。From Gelman, Pearl’s obnoxiousness obstructs the disemmination of his ideas. And works by economists are swept under the rug. 画图容易，但用Rubin亦可。同样的问题仍是我们有哪些x该放进来？然后如何从ate到更有意义的参数是根本的识别问题也是modelling problem，这个用图难以。另外经济学家最大的一个贡献（语出Hausman）就是sem；Pearl似乎不能领会我们为何要用sem。端看pearl能不能用dag来写一个市场均衡模型. Imbens最近写了一篇review说经济学家们不用学图论用处不多

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让我这个很想粗浅了解统计学的人是一个很好的入门教材。从经典统计学，到贝叶斯，到因果关系都是有很好的介绍。里面的例子很有趣也很烧脑，虽然不知道如何直接利用里面的公式，但是至少知道在统计学之外还有别的工具可以使用。

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