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Introduction to Stochastic Programming – Springer Series in Operations Research
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Dynamic Programming for Economists: From Basic Growth Models to Computational Methods (Routledge-Giappichelli Studies in Business and Management)
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Mastering data.table in R: Programming Techniques for Data Science (Chapman & Hall/CRC The R Series)
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Practical Data Analysis and Statistics: Hands-On with Python and Manual Calculations A Complete Guide to Descriptive Statistics, Probability, Inference, Hypothesis Testing, and Regression
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Introduction to Mathematical Programming: Applications and Algorithms
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Mastering data.table in R: Programming Techniques for Data Science (Chapman & Hall/CRC The R Series)
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Demystifying Probability and Statistics for Data Scientists with R
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Hacking Luck: RNG Manipulation and the Mathematical Deconstruction of Video Game Probability
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Python for Probability, Statistics, and Machine Learning
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Fenchel and Disjunctive Decomposition for Stochastic Mixed-Integer Programming (Springer Optimization and Its Applications, 231)
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Mathematical Infinity: The Probability Matrices of Markov Chains: States, Transitions, and the Procedural Generation of Infinite Virtual Worlds
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Demystifying Probability and Statistics for Data Scientists with R
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