圖書標籤: 統計 邏輯 方法論 計算機 因果 哲學 科普 AI
发表于2024-08-02
The Book of Why pdf epub mobi txt 電子書 下載 2024
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.
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.
總算有本Judea Pearl的書是我能看懂的瞭,雖然是科普……讀下來的感覺,Pearl的工作將人類直覺化的因果推理能力用數學形式錶達瞭齣來,使causal effect成為可以估計的變量。但因果模型如何提齣,如何驗證,似乎並沒有涉及太多。如果強人工智能需要學會因果推理,提齣模型應該比估算模型要難得多,也重要得多。
評分去年nips有眼不識泰山沒去聽老爺子的talk,作為初級煉丹工看這本麵嚮大眾的新書補課也很開眼界。“相關不蘊涵因果”講得多瞭都不知道所謂因果關係究竟是什麼。僅靠擬閤數據,不管是用深度學習還是多fancy的方法,都無法錶示因果關係;要談論因果乃至虛擬事實,須明確引入數據以外的假設,而書中也指明瞭什麼樣的假設配上什麼樣的數據可以迴答什麼樣的因果問題。現實生活中很多問題都不能做隨機對照試驗,這套理論也因此格外重要。要是老爺子再談談他對強化學習的看法就好瞭。
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。。。
評分每個人都是一部因果關係自動機。真要把人腦對因果的思維過程掰扯明白,還真是不容易。作者的因果模型,是把復雜問題簡單化的經典例子瞭。
評分詳細解讀瞭相關性和因果性的本質區彆,提齣瞭基於數學推導,結閤symobolic的人類知識和numerical的數據的解決方法
这些人发明了如此简单而常用的东西,以至所有人都忘了这些东西也需要人发明出来。 非常匆忙地读了一遍之后,脑子里第一时间浮现的是小说《好兆头》里的这句话,它基本上是我对这本书印象的完美概括。 经济学专业的学生,如果选过一些 policy evaluation 和 causal inference 方...
評分 評分 評分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...
評分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 ...
The Book of Why pdf epub mobi txt 電子書 下載 2024