The Book of Why pdf epub mobi txt 電子書下載 2024

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Judea Pearl

Basic Books

2018-5-15

432

USD 32.00

Hardcover

9780465097609

圖書標籤: 統計邏輯方法論計算機因果哲學科普 AI

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发表于2024-09-27

The Book of Why epub 下載 mobi 下載 pdf 下載 txt 電子書下載 2024

The Book of Why pdf epub mobi txt 電子書下載 2024

圖書描述

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 下載 mobi epub pdf txt 電子書

著者簡介

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.

圖書目錄

The Book of Why pdf epub mobi txt 電子書下載

想要找書就要到小哈圖書下載中心

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用戶評價

評分☆☆☆☆☆

很不錯，很受啓發。其實語言限製思維這個簡單的事情也很有意思。說個身邊的例子，很多人說深圳要取代香港，卻不知道深圳何以成為深圳。當年鄧公畫瞭五個特區，隻有一個成功瞭。稍微動腦子問一下why就知道深圳成功的唯一原因就是香港。去年香港打瞭個噴嚏，深圳就半癱瘓瞭。這兩個不可分割的玩意，竟然有一方把另一方當作對手。。。

評分☆☆☆☆☆

學統計教統計十幾年，好多核心的概念第一次看人講得這麼清楚，豁然開朗豁然開朗！

評分☆☆☆☆☆

從公司圖書館藉得此書，翻瞭前兩章，結閤得到上萬維鋼的講解，大緻瞭解瞭因果關係的重要性和對下一步強AI的啓發，為什麼要超越相關性去探求因果性。如作者在前言末尾講到的：“Data do not understand cause and effects; human do. I hope that the new science of casual inference will enable us to better understand how we do it, because there is no better way to understand ourselves than by emulating ourselves. ”

評分☆☆☆☆☆

知其所以然。