Probability Theory: The Logic of Science

Probability Theory: The Logic of Science

By
E.T. Jaynes
E.T. Jaynes
1999 • 753 pages

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15 books

Computer Science And Math

ann
Anna
Calculus
How to Prove It A Structured Approach
Algorithms to Live By: The Computer Science of Human Decisions
Probability Theory: The Logic of Science
Calculus Made Easy
Concrete Mathematics
How to Lie with Statistics

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25 books

Rationality

panashe
Panashe Fundira
Good and Real: Demystifying Paradoxes from Physics to Ethics
Thinking and Deciding
Probability Theory: The Logic of Science
Rationality and the Reflective Mind
How to Measure Anything
Mathematics and the Search for Knowledge

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441 books

Dot

boson
Boson
The America's Test Kitchen Cooking School Cookbook: Everything You Need to Know to Become a Great Cook
Pattern Recognition and Machine Learning
The Intelligent Investor
The Information: A History, a Theory, a Flood
Hacking
Autobiography of a yogi
The Annotated Turing

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11 books

Maths

r0h1t4sh
Rohitash Kumar
How Not to Be Wrong: The Power of Mathematical Thinking
Introduction to Topology
Proofs from the Book
Naive Set Theory
Conceptual Mathematics
Linear Algebra Done Right

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17,813 books

My Library

Nitin
Nitin Rughoonauth
Fermi Remembered
Goedel's Way: Exploits into an undecidable world
Brave Genius: A Scientist, a Philosopher, and Their Daring Adventures from the French Resistance to the Nobel Prize
Debate en torno a la etica del discurso de Apel: Diálogo filosófico Norte-Sur desde América Latina
Love and math : the heart of hidden reality
The Road to Reality
The Large, the Small and the Human Mind

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22 books

Career

glitsyn
Glitsyn
Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making
Strong Towns
Escaping the Housing Trap: The Strong Towns Response to the Housing Crisis
Probability Theory: The Logic of Science
Modeling Mindsets: The Many Cultures Of Learning From Data
Supervised Machine Learning for Science: How to stop worrying and love your black box

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18 books

Data Analysis

glitsyn
Glitsyn
Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making
Supervised Machine Learning for Science: How to stop worrying and love your black box
Statistical Rethinking: A Bayesian Course with Examples in R and Stan
INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS.
Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information