Audit Analytics : Data Science for the Accounting Profession
J. Christopher Westland
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Linear Algebra for Data Science, Machine Learning, and Signal Processing
Jeffrey A. (University of Michigan, Ann Arbor) Fessler
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Acta Numerica 2024: Volume 33
Douglas (University of Minnesota) Arnold
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Regression Modeling Strategies : With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Jr., Frank E. Harrell
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The Algorithm Design Manual
Steven S. Skiena
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An Intermediate Course in Probability
Allan Gut
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Graph Theory
Reinhard Diestel
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An Invitation to Combinatorics
Shahriar (Pomona College, California) Shahriari
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The 9 Pitfalls of Data Science
Gary (Fletcher Jones Professor of Economics, Fletcher Jones Pro Smith
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Python for Probability, Statistics, and Machine Learning
Jose Unpingco
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Linear Algebra And Optimization With Applications To Machine Learning - Volume Ii: Fundamentals Of Optimization Theory With Applications To Machine Learning
Jean H (Univ Of Pennsylvania, Usa) Gallier
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Machine Learning
Zhi-Hua, PhD Zhou
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Basic Elements of Computational Statistics
Wolfgang Karl Hardle
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The Nature of Complex Networks
Sergey N. (Researcher, Researcher, Department of Physics, Dorogovtsev
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Understand Mathematics, Understand Computing : Discrete Mathematics That All Computing Students Should Know
Arnold L. Rosenberg
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An Introduction to Machine Learning
Miroslav Kubat
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A Course in Mathematical Statistics and Large Sample Theory
Rabi Bhattacharya
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Probability and Statistics for Computer Scientists
Michael (American University, Washington, DC) Baron
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Monte Carlo Methods
Adrian Barbu
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Discrete Mathematics : A Concise Introduction
George Tourlakis
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Matrix Algebra : Theory, Computations and Applications in Statistics
James E. Gentle
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Application-Specific Arithmetic : Computing Just Right for the Reconfigurable Computer and the Dark Silicon Era
Florent de Dinechin
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Graphs and Combinatorial Optimization: from Theory to Applications : CTW 2023, Garmisch-Partenkirchen, Germany, June 20–22
Andreas Brieden
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Petri Net Primer : A Compendium on the Core Model, Analysis, and Synthesis
Eike Best
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