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Synopsis
An argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence.
"Illuminating." ―New York Times
"Extraordinary." ―Science Friday
“Correlation is not causation.” This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past.
The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis. Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes.
Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and scientists alike, providing tools to explore the observable world and worlds that might have been.
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About the Author
Judea Pearl is chancellor’s professor of computer science at UCLA. The author of three foundational books in AI, he has won numerous awards, including the Alan Turing Award. He lives in Los Angeles, California.
Dana Mackenzie is a PhD mathematician turned science writer. He has written or co-written fourteen books, mostly on mathematical topics. He lives in Santa Cruz, California.
"About this title" may belong to another edition of this title.
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Paperback. Condition: new. Paperback. An argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence. "Illuminating." --New York Times "Extraordinary." --Science Friday "Correlation is not causation." This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past. The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis. Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes. Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and scientists alike, providing tools to explore the observable world and worlds that might have been. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781541608986
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Taschenbuch. Condition: Neu. Neuware - An argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence.'Illuminating.' -New York Times'Extraordinary.' -Science Friday 'Correlation is not causation.' This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past. The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis. Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes. Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and scientists alike, providing tools to explore the observable world and worlds that might have been. Seller Inventory # 9781541608986
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Paperback. Condition: new. Paperback. An argument for how understanding causality has revolutionized science and will revolutionize artificial intelligence. "Illuminating." --New York Times "Extraordinary." --Science Friday "Correlation is not causation." This mantra, chanted by scientists for more than a century, once led to a virtual prohibition on causal talk. Today, with causal analysis taking center stage in AI and other applications, the old taboos are a thing of the past. The causal revolution, instigated by Judea Pearl and others, established causality on a firm scientific basis. Pearl showed how intuitive models can interface with data to help answer causal questions, such as whether a drug will cure an illness or, counterfactually, whether an illness would have persisted absent the drug. These models provide a blueprint for causal AI to learn and take responsibility for its mistakes. Updated with a new preface and summary of recent advances, The Book of Why outlines the basics of cause and effect for lay readers and scientists alike, providing tools to explore the observable world and worlds that might have been. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781541608986
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