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Numerical Methods for Finance
Featuring international contributors from both industry and academia, Numerical Methods for Finance explores new and relevant numerical methods for the solution of practical problems in finance. It is one of the few books entirely devoted to numerical methods as applied to the financial field.

Presenting state-of-the-art methods in this area, the book first discusses the coherent risk measures theory and how it applies to practical risk management.
Mathematica� Programming: an Advanced Introduction
Starting from first principles, this book covers all of the foundational material needed to develop a clear understanding of the Mathematica language, with a practical emphasis on solving problems. Concrete examples throughout the text demonstrate how Mathematica language, can be used to solve problems in science, engineering, economics/finance, computational linguistics, geoscience, bioinformatics, and a range of other fields.

Discrete Mathematics with Algorithms
This is a first-year course in discrete mathematics requireing no calculus or computer programming experience.

Theory of Statistics
This book is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations. In addition, students at this level should acquire, or begin acquiring, a deep appreciation for the field, including its historical development and its relation to other areas of mathematics and science generally.

Set Theoretic Approach to Algebraic Structures in Mathematics - A Revelation
This book brings out how sets in algebraic structures can be used to construct the most generalized algebraic structures, like set linear algebra / vector space, set ideals in groups and rings and semigroups, and topological set vector spaces. This sort of study is innovative and will find applications in data handling.
Algebra: A Computational Introduction
Adequate texts that introduce the concepts of abstract algebra are plentiful. None, however, are more suited to those needing a mathematical background for careers in engineering, computer science, the physical sciences, industry, or finance than Algebra: A Computational Introduction. Along with a unique approach and presentation, the author demonstrates how software can be used as a problem-solving tool for algebra.

Advanced High-School Mathematics
An advanced mathematics textbook accessible by and interesting to a relatively advanced high-school student. Topics: geometry, discrete mathematics, abstract algebra, series and ordinary differential equations, and inferential statistics.
Elementary Algebra
Elementary Algebra is a texbookt that covers the traditional topics studied in a modern elementary algebra course. It is intended for students who (1) have no exposure to elementary algebra, (2) have previously had an unpleasant experience with elementary algebra, or (3) need to review algebraic concepts and techniques.
From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science
This is a textbook for a course in mathematical probability and statistics for computer science students. Computer science examples are used throughout, in areas such as: computer networks; data and text mining; computer security; remote sensing; computer performance evaluation; software engineering; data management; etc.
The Nature of Code: Simulating Natural Systems with Processing
How can we capture the unpredictable evolutionary and emergent properties of nature in software? How can understanding the mathematical principles behind our physical world help us to create digital worlds?

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