Math and Architectures of Deep Learning
Krishnendu Chaudhury
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Math For Security : From Graphs and Geometry to Spatial Analysis
Daniel Reilly
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Introduction to Probability and Statistics for Data Science : with R
Steven E. (Saint Louis University, Missouri) Rigdon
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Mathematical Introduction to Data Science
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Douglas (University of Minnesota) Arnold
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Theory and Applications of Time Series Analysis and Forecasting : Selected Contributions from ITISE 2021
Olga Valenzuela
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Audit Analytics : Data Science for the Accounting Profession
J. Christopher Westland
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Foundations of Software Science and Computation Structures : 27th International Conference, FoSSaCS 2024, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2024,
Naoki Kobayashi
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R-Calculus, IV: Propositional Logic
Wei Li
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Essential Math for Data Science : Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics
Thomas Nield
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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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An Intermediate Course in Probability
Allan Gut
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Discrete and Combinatorial Mathematics : Pearson New International Edition
Ralph Grimaldi
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Graph Theory
Reinhard Diestel
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AQA GCSE 9-1 Maths Higher Practice Papers : Ideal for the 2024 and 2025 Exams
Collins GCSE
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Introduction to Data Science : A Python Approach to Concepts, Techniques and Applications
Laura Igual
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Statistical Learning with Math and Python : 100 Exercises for Building Logic
Joe Suzuki
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An Invitation to Combinatorics
Shahriar (Pomona College, California) Shahriari
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Geometric Multiplication of Vectors : An Introduction to Geometric Algebra in Physics
Miroslav Josipovic
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The 9 Pitfalls of Data Science
Gary (Fletcher Jones Professor of Economics, Fletcher Jones Pro Smith
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Logical Methods : The Art of Thinking Abstractly and Mathematically
Roger Antonsen
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Deep Generative Modeling
Jakub M. Tomczak
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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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