Logo

Mathematics for Computer Scientists

Small book cover: Mathematics for Computer Scientists

Mathematics for Computer Scientists
by

Publisher: BookBoon
ISBN-13: 9788776814267
Number of pages: 153

Description:
In this textbook you will find the basic mathematics that is needed by computer scientists. The author will help you to understand the meaning and function of mathematical concepts. The best way to learn it, is by doing it, the exercises in this book will help you do just that. Subjects as Elementary logic, factorization, plotting functions and matrices are explained.

Home page url

Download or read it online for free here:
Download link
(3.9MB, PDF)

Similar books

Book cover: Art Gallery Theorems and AlgorithmsArt Gallery Theorems and Algorithms
by - Oxford University Press
Art gallery theorems and algorithms are so called because they relate to problems involving the visibility of geometrical shapes and their internal surfaces. This book explores generalizations and specializations in these areas.
(18596 views)
Book cover: Mathematical Illustrations: A Manual of Geometry and PostScriptMathematical Illustrations: A Manual of Geometry and PostScript
by - Cambridge University Press
The author gives an introduction to basic features of the PostScript language and shows how to use it for producing mathematical graphics. The book includes the discussion computer graphics and some comments on good style in mathematical illustration.
(19510 views)
Book cover: Axiom: The Scientific Computation SystemAxiom: The Scientific Computation System
by - axiom-developer.org
Axiom is a free general purpose computer algebra system. The book gives a technical introduction to AXIOM, interacts with the system's tutorial, accesses algorithms developed by the symbolic computation community, and presents advanced techniques.
(20645 views)
Book cover: Probabilistic Programming and Bayesian Methods for HackersProbabilistic Programming and Bayesian Methods for Hackers
by - GitHub, Inc.
This book is designed as an introduction to Bayesian inference from a computational understanding-first, and mathematics-second, point of view. The book assumes no prior knowledge of Bayesian inference nor probabilistic programming.
(20760 views)