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Authors: Sławomir Gryś (2024) - This book provides an accessible overview of common data formats used to write numbers in programming languages and how the computer performs four basic arithmetic operations from the point of view of the processor instruction set. The book is primarily didactic in nature, therefore the theoretical information is enriched with many numerical examples and exercises to be solved using a "sheet of paper and a pencil".
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Authors: Masoud Makrehchi (2024) - The book guides you through essential aspects of algorithm design and analysis, including proving correctness and the importance of repetition and loops. This groundwork sets the stage for exploring algorithm complexity, with practical exercises in design and analysis using sorting and search as examples.
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Authors: Howard Anton (2019) - Cuốn sách được thiết kế cho sinh viên đại học năm nhất, nhằm giới thiệu các khái niệm cơ bản của đại số tuyến tính một cách rõ ràng và dễ hiểu. Nội dung không yêu cầu kiến thức về giải tích, nhưng có bao gồm các bài tập và ví dụ dành cho những sinh viên đã học giải tích, được đánh dấu rõ ràng và có thể bỏ qua mà không ảnh hưởng đến mạch kiến thức.
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Authors: Crista Arangala (2025) - This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition and connections to differential equations
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Authors: Satya N. Mukhopadhyay (2025) - It acts as a pivotal link bridging the Riemann integral and the Lebesgue integral, with a primary focus on tracing the evolution of measure and integration from their historical roots. A distinctive feature of the book is meticulous guidance, providing a step-by-step journey through the subject matter, thus rendering complex concepts more accessible to beginners
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Authors: Ashkan Nikeghbali (2025) - This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.
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Authors: - (2013) - The Mathematical Sciences in 2025 examines the current state of the mathematical sciences and explores the changes needed for the discipline to be in a strong position and able to maximize its contribution to the nation in 2025.
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Authors: Todd Arbogast (2025) - This is a self-contained volume providing a rigorous introduction to functional analysis and its applications. Students from mathematics, science, engineering, and certain social science and interdisciplinary programs will benefit from the material. It is accessible to graduate and advanced undergraduate students with a solid background in undergraduate mathematics and an appreciation of mathematical rigor.
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Authors: William P. Fox (2025) - The modeling prospective reveals the practical relevance of the numerical methods in context to real world problems. At the core of this text are the real-world modeling projects. Chapters are introduced and techniques are discussed with common examples. A modeling scenario is introduced that will be solved with these techniques later in the chapter.
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Authors: Mark J. DeBonis. (2025) - A Beginner's Guide to Mathematical Proof prepares mathematics majors for the transition to abstract mathematics, as well as introducing a wider readership of quantitative science students, such as engineers, to the mathematical structures underlying more applied topics
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Authors: Douglas Cenzer (2025) - It gives a solid introduction to axiomatic set theory and presents several interesting applications." MathSciNet This book presents both axiomatic and descriptive set theory, targeting upper-level undergraduate and beginning graduate students. It aims to equip them for advanced studies in set theory, mathematical logic, and other mathematical fields, including analysis, topology, and algebra.
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Authors: Fabian Waleffe. (2025) - Vector and complex calculus are essential for applications to electromagnetism, fluid and solid mechanics, and the differential geometry of surfaces. The standard multivariable calculus courses are largely limited to 'xyz' calculus, but vector calculus is about geometric concepts invariant under coordinate transformations. This textbook takes the students from the geometry and algebra of vectors, to the key concepts and tools of vector calculus, including differential geometry of curves and surfaces, curvilinear coordinates, and capping off with a study of the essential elements of the calculus of functions of one complex variable.
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Authors: Gérard-Michel Cochard (2025) - The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics
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Authors: Hebert Montegranario (2025) - This textbook introduces variational calculus and regularization methods for inverse problems, seamlessly blending classical concepts with contemporary computational applications, particularly in the field of image processing. The classical perspective draws upon foundational topics explored by pioneers such as Euler and Lagrange, establishing a solid theoretical groundwork.
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Authors: Lars Tuset (2025) - This book is a concise, self-contained treatise on abstract algebra with an introduction to number theory, where students normally encounter rigorous mathematics for the first time. The authors build up things slowly, by explaining the importance of proofs. Number theory with its focus on prime numbers is then bridged via complex numbers and linear algebra, to the standard concepts of a course in abstract algebra, namely groups, representations, rings, and modules.
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Authors: M. A. Hooshyar (2025) - This book is based on lecture notes for a numerical analysis course designed mainly for senior undergraduate students majoring in mathematics, engineering, computer science and physical sciences. The book has two overarching goals.
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Authors: Naokant Deo (2024) - This book is a straightforward and comprehensive presentation of the concepts and methodology of elementary real analysis. Targeted to undergraduate students of mathematics and engineering, it serves as the foundation for mathematical reasoning and proofs.
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Authors: Peter Brusov (2025) - This textbook is designed to facilitate a thorough learning for students of financial mathematics. It includes exercises and theoretical questions across seven chapters: Interest Theory, Financial Flows and Annuities, Profitability and Risk of Financial Operations, Portfolio Analysis, Bonds, Modigliani-Miller Theory, and Brusov-Filatova-Orekhova Theory.
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Authors: Ronald T. Kneusel (2024) - In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms
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Authors: Joshua Chan (2025) - The 2nd edition changes the programming language used in the text from MATLAB to Julia. For all examples with computing components, the authors provide data sets and their own Julia codes.
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