**Mathematics for Computer Scientists**

by Gareth J. Janacek, Mark L. Close

**Publisher**: BookBoon 2008**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.

Download or read it online for free here:

**Download link**

(3.9MB, PDF)

## Similar books

**Think Stats: Probability and Statistics for Programmers**

by

**Allen B. Downey**-

**Green Tea Press**

Think Stats is an introduction to Probability and Statistics for Python programmers. This new book emphasizes simple techniques you can use to explore real data sets and answer interesting statistical questions. Basic skills in Python are assumed.

(

**22736**views)

**Probabilistic Programming and Bayesian Methods for Hackers**

by

**Cameron Davidson-Pilon**-

**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.

(

**22882**views)

**Implementing Mathematics with The Nuprl Proof Development System**

by

**R. L. Constable, at al.**-

**Prentice Hall**

The authors offer a tutorial on the new mathematical ideas which underlie their research. Many of the ideas in this book will be accessible to a well-trained undergraduate with a good background in mathematics and computer science.

(

**17190**views)

**Mathematics for Algorithm and Systems Analysis**

by

**Edward A. Bender, S. Gill Williamson**-

**Dover Publications**

This text assists undergraduates in mastering the mathematical language to address problems in the field's many applications. It consists of 4 units: counting and listing, functions, decision trees and recursion, and basic concepts of graph theory.

(

**31351**views)