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Elements of Information Theory

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From Amazon: “The Second Edition of this fundamental textbook maintains the book’s tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide reads with a solid understanding of the underlying theory … Continue Reading

Probability: Theory and Examples

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From Amazon: “This book is an introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems.”

Probability and Random Processes

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From Amazon: “This book gives an introduction to probability and its many practical applications by providing a thorough, entertaining account of basic probability and important random processes, covering a range of important topics. Emphasis is on modelling rather than abstraction and there are new sections on sampling and Markov chain Monte Carlo, renewal-reward, queuing networks, stochastic calculus, and option pricing in the Black-Scholes model for financial markets. In addition, there … Continue Reading

Bayesian Data Analysis

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From Amazon: “Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors–all leaders in the statistics community–introduce … Continue Reading

Introduction to Nonparametric Estimation

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From Amazon: “This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore the results are not always given in the most general form but rather under assumptions that lead to shorter or more elegant … Continue Reading

Asymptotic Statistics (Cambridge Series in Statistical and Probabilistic Mathematics)

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From Amazon: “Here is a practical and mathematically rigorous introduction to the field of asymptotic statistics. In addition to most of the standard topics of an asymptotics course–likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures–the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, … Continue Reading

Statistical Inference

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From Amazon: “This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background. It can also be … Continue Reading

Practical Recommender Systems

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Covers how recommender systems work and how to create them for a website.

Fluent Python: Clear, Concise, and Effective Programming

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From Amazon: “Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best–and possibly most neglected–features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. … Continue Reading

No Bullshit Guide to Math and Physics

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From Amazon: “Often calculus and mechanics are taught as separate subjects. It shouldn’t be like that. Learning calculus without mechanics is incredibly boring. Learning mechanics without calculus is missing the point. This textbook integrates both subjects and highlights the profound connections between them. This is the deal. Give me 350 pages of your attention, and I’ll teach you everything you need to know about functions, limits, derivatives, integrals, vectors, forces, … Continue Reading