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  • Sách/Book

  • Elementary linear algebra

    • 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.
  • Sách/Book

  • Set theory and foundations of mathematics : an introduction to mathematical logic

    • 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.
  • Sách/Book

  • Measure and integration : an introduction

    • 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
  • Sách/Book

  • Abstract algebra via numbers

    • 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.
  • Sách/Book

  • Statistical modeling and computation

    • 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.
  • Sách/Book

  • Numerical methods and analysis with mathematical modelling

    • 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.
  • Sách/Book

  • Machine learning : from the classics to deep networks, transformers, and diffusion models

    • Authors: Sergios Theodoridis (2025)

  • Third Edition starts with the basics, including least squares regression and maximum likelihood methods, Bayesian decision theory, logistic regression, and decision trees. It then progresses to more recent techniques, covering sparse modelling methods, learning in reproducing kernel Hilbert spaces and support vector machines. Bayesian learning is treated in detail with emphasis on the EM algorithm and its approximate variational versions with a focus on mixture modelling, regression and classification.
  • Sách/Book

  • Vector and complex calculus : a textbook for students of the physical sciences

    • 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.
  • Sách/Book

  • Introduction to mathematical analysis

    • 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.
  • Sách/Book

  • Mathematics for digital science 1 : fundamentals Vol.1 Fundamentals

    • 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