The Book of Why 2024 pdf epub mobi 電子書 下載


The Book of Why

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The Book of Why pdf epub mobi 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.


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

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發表於2024-11-25

The Book of Why 2024 pdf epub mobi 電子書 下載

The Book of Why 2024 pdf epub mobi 電子書 下載

The Book of Why 2024 pdf epub mobi 電子書 下載



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出版者:Basic Books
作者:Judea Pearl
出品人:
頁數:432
譯者:
出版時間:2018-5-15
價格:USD 32.00
裝幀:Hardcover
isbn號碼:9780465097609
叢書系列:

圖書標籤: 統計  邏輯  方法論  計算機  因果  哲學  科普  AI   


The Book of Why 2024 pdf epub mobi 電子書 下載
想要找書就要到 本本書屋
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

The Book of Why pdf epub mobi 用戶評價

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知其所以然。

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Strong AI和Causal Effect僅依靠當前的統計、機器學習和深度學習方法是不夠的,需要建立一套能描述Causal Effect的數學化的語言,在此基礎上纔能由現在的rung one(描述association)走到rung two(以do-clause描述和推斷intervention後産生的結果)和rung three(描述和推斷what if have done的結果,即如果做某事後産生的結果,而該事件實際並不一定會發生,而這是人類具備的聯想和推斷齣未知事物因果關係的能力,目前的弱AI並不具備)。深度學習隻是一個黑盒,存在可解釋性以及仍是一種弱AI的問題。且對因果關係而非相關關係的描述和研究在其他領域也非常需要。

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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。

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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!

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學習一哈

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