Modern Fortran Explained : Incorporating Fortran 2023
Mr Michael (Formerly of CERN, Geneva, Switzerland) Metcalf
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Graph Algorithms for Data Science
Tomaz Bratanic
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Enumerative Combinatorics: Volume 2
Richard (Massachusetts Institute of Technology) Stanley
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Cryptanalysis
Helen Fouche Gaines
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Essential Maths Skills for AS/A Level Computer Science
Victoria Ellis
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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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All of Statistics : A Concise Course in Statistical Inference
Larry Wasserman
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Foundation Mathematics for Computer Science : A Visual Approach
John Vince
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An Invitation to Combinatorics
Shahriar (Pomona College, California) Shahriari
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Deep Generative Modeling
Jakub M. Tomczak
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Machine Learning
Zhi-Hua, PhD Zhou
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An Introduction to Machine Learning
Miroslav Kubat
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Scientific Computing : For Scientists and Engineers
Timo Heister
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Beginning R 4 : From Beginner to Pro
Matt Wiley
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Modularity and Dynamics on Complex Networks
Renaud (University of Oxford) Lambiotte
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The Shortest Path to Network Geometry : A Practical Guide to Basic Models and Applications
M. Angeles (University of Barcelona, University of Barcelona Serrano
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Multivariate Data Analysis on Matrix Manifolds : (with Manopt)
Nickolay Trendafilov
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A Guide to Graph Algorithms
Ton Kloks
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Modern Cryptography Volume 1 : A Classical Introduction to Informational and Mathematical Principle
Zhiyong Zheng
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Core Data Analysis: Summarization, Correlation, and Visualization
Boris Mirkin
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Graph Drawing and Network Visualization : 27th International Symposium, GD 2019, Prague, Czech Republic, September 17–20, 2019, Proceedings
Daniel Archambault
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Algebra and Geometry with Python
Sergei Kurgalin
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Simulation and Inference for Stochastic Processes with YUIMA : A Comprehensive R Framework for SDEs and Other Stochastic Processes
Stefano M. Iacus
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Graph Data Management : Fundamental Issues and Recent Developments
George Fletcher
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