**Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics**

by Justin Solomon

**Publisher**: CRC Press 2015**ISBN/ASIN**: 1482251884**Number of pages**: 397

**Description**:

This book presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.

Download or read it online for free here:

**Download link**

(17MB, PDF)

## Similar books

**Mathematical Illustrations: A Manual of Geometry and PostScript**

by

**Bill Casselman**-

**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.

(

**21992**views)

**Art Gallery Theorems and Algorithms**

by

**Joseph O'Rourke**-

**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.

(

**21303**views)

**Computer Algebra, Algorithms, Systems and Applications**

by

**Richard Liska, at al.**-

**Czech Technical University**

From the table of contents: Introduction; Algorithms for algebraic computation; Integrated mathematical systems; Basic possibilities of integrated mathematical systems; Applications of computer algebra; Another sources of study.

(

**18658**views)

**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.

(

**23658**views)