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The equation of knowledge : from Bayes' rule to a unified philosophy of science / Lê Nguyên Hoang.

By: Hoang, Lê Nguyên [author.].
Material type: materialTypeLabelBookPublisher: Boca Raton, FL : CRC, 2020Edition: First edition.Description: 1 online resource illustrations (black and white).Content type: text Media type: computer Carrier type: online resourceISBN: 9780367855307; 0367855305; 9781000063271; 1000063275; 9781000063233; 1000063232.Uniform titles: Formule du savoir. English. Subject(s): Bayesian statistical decision theory | Knowledge, Theory of | Mathematics -- Philosophy | Science -- Methodology | MATHEMATICS / History & Philosophy | MATHEMATICS / Probability & Statistics / Bayesian Analysis | MATHEMATICS / Recreations & GamesDDC classification: 519.5/42 Online resources: Taylor & Francis | OCLC metadata license agreement
Contents:
Foreword / Gilles Dowek -- On a transformative journey -- Bayes theorem -- Logically speaking... -- Let's generalize! -- All hail prejudices -- The Bayesian prophets -- Solomonoff's demon -- Can you keep a secret? -- Game, set and math -- Will Darwin select Bayes? -- Exponentially counter-intuitive -- Ockham cuts to the chase -- Facts are misleading -- Quick and not too dirty -- Wish me luck -- Down memory lane -- Let's sleep on it -- The unreasonable effectiveness of abstraction -- The Bayesian brain -- It's all fictions -- Exploring the origins of beliefs -- Beyond Bayesianism.
Summary: The Equation of Knowledge: From Bayes' Rule to a Unified Philosophy of Science introduces readers to the Bayesian approach to science: teasing out the link between probability and knowledge. The author strives to make this book accessible to a very broad audience, suitable for professionals, students, and academics, as well as the enthusiastic amateur scientist/mathematician. This book also shows how Bayesianism sheds new light on nearly all areas of knowledge, from philosophy to mathematics, science and engineering, but also law, politics and everyday decision-making. Bayesian thinking is an important topic for research, which has seen dramatic progress in the recent years, and has a significant role to play in the understanding and development of AI and Machine Learning, among many other things. This book seeks to act as a tool for proselytising the benefits and limits of Bayesianism to a wider public. Features Presents the Bayesian approach as a unifying scientific method for a wide range of topics Suitable for a broad audience, including professionals, students, and academics Provides a more accessible, philosophical introduction to the subject that is offered elsewhere
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"A Chapman & Hall book."

Translation of: La formule du savoir : une philosophie unifiée du savoir fondée sur le théorème de Bayes.

Foreword / Gilles Dowek -- On a transformative journey -- Bayes theorem -- Logically speaking... -- Let's generalize! -- All hail prejudices -- The Bayesian prophets -- Solomonoff's demon -- Can you keep a secret? -- Game, set and math -- Will Darwin select Bayes? -- Exponentially counter-intuitive -- Ockham cuts to the chase -- Facts are misleading -- Quick and not too dirty -- Wish me luck -- Down memory lane -- Let's sleep on it -- The unreasonable effectiveness of abstraction -- The Bayesian brain -- It's all fictions -- Exploring the origins of beliefs -- Beyond Bayesianism.

The Equation of Knowledge: From Bayes' Rule to a Unified Philosophy of Science introduces readers to the Bayesian approach to science: teasing out the link between probability and knowledge. The author strives to make this book accessible to a very broad audience, suitable for professionals, students, and academics, as well as the enthusiastic amateur scientist/mathematician. This book also shows how Bayesianism sheds new light on nearly all areas of knowledge, from philosophy to mathematics, science and engineering, but also law, politics and everyday decision-making. Bayesian thinking is an important topic for research, which has seen dramatic progress in the recent years, and has a significant role to play in the understanding and development of AI and Machine Learning, among many other things. This book seeks to act as a tool for proselytising the benefits and limits of Bayesianism to a wider public. Features Presents the Bayesian approach as a unifying scientific method for a wide range of topics Suitable for a broad audience, including professionals, students, and academics Provides a more accessible, philosophical introduction to the subject that is offered elsewhere

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