 Veridical Data Science: The Practice of Responsible Data Analysis and Decision Making
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 Interpretable Machine Learning Interpretable Machine Learning: A Guide For Making Black Box Models Explainable
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 Supervised Machine Learning for Science: How to stop worrying and love your black box
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 Statistical Rethinking: A Bayesian Course with Examples in R and Stan
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 INFORMATION THEORY, INFERENCE, AND LEARNING ALGORITHMS.
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 Elements of Information Theor 2nd (second) edition Text Only Elements of Information Theor 2nd (second) edition Text Only
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 Foundations of Info-Metrics: Modeling, Inference, and Imperfect Information
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 Advances in Info-Metrics: Information and Information Processing across Disciplines | 1 read |
 Regression and Other Stories
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 Bayesian Data Analysis
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 A First Course in Causal Inference
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 Causality Causality: Models, Reasoning and Inference
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 Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more
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 Bernoulli's Fallacy: Statistical Illogic and the Crisis of Modern Science
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 New Foundations for Information Theory: Logical Entropy and Shannon Entropy
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 Probability Theory: The Logic of Science
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 The Simple and Infinite Joy of Mathematical Statistics
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 Modeling Mindsets: The Many Cultures Of Learning From Data
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