Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics
by Justin Solomon
Publisher: CRC Press 2015
Number of pages: 397
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.
Home page url
Download or read it online for free here:
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.
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.
by S. Basu, R. Pollack, M. Roy - Springer
The monograph gives a detailed exposition of the algorithmic real algebraic geometry. It is well written and will be useful both for beginners and for advanced readers, who work in real algebraic geometry or apply its methods in other fields.
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.