The Book of Why pdf epub mobi txt 电子书 下载 2024


The Book of Why

简体网页||繁体网页
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2024-05-10

The Book of Why epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

The Book of Why epub 下载 mobi 下载 pdf 下载 txt 电子书 下载 2024

The Book of Why pdf epub mobi txt 电子书 下载 2024



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.


图书目录


The Book of Why pdf epub mobi txt 电子书 下载
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用户评价

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学习一哈

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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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学习一哈

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详细解读了相关性和因果性的本质区别,提出了基于数学推导,结合symobolic的人类知识和numerical的数据的解决方法

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读后感

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The ladder of causation Association Predictions based on passive observations Intervention Involving not just seeing but changing what is Counterfactuals Not only experiments, but also need the model of the underlying causal process--"theory" or "a law of n...  

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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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rather than a new science. 1,作者并没有区分自然科学和社会以及行为科学,没有讨论这两个领域因果推断的异同,也没有上升到科学哲学的层面讨论因果推断本身。这些本身都不是问题。只是就内容来说,书中的science实际上指的是社会科学和行为科学,作者所说的“因果革命 (the ...  

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一 五月,腾讯稳坐公司新闻头条,与今日头条互诉,腾讯视频打造的女团选拔节目《创造101》中的选手王菊逆袭翻盘,现象级的王菊效应在网上发酵。在五月,让我最感兴趣的一条公司新闻也与腾讯有关。5月30日,腾讯官方公众号发布了一篇文章,标题是《她叫Siren,不是人,也可以是...  

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