Linear Algebra and Probability for Computer Science Applications

Assuming as little mathematical background as possible, this classroom-tested text focuses on mathematical techniques that are most relevant to computer scientists. It covers applications from computer graphics, web search, machine learning, cryptography, and a host of other computer science areas. After an introductory chapter on MATLAB®

List of contents

MATLAB. LINEAR ALGEBRA: Vectors. Matrices. Vector Spaces. Algorithms. Geometry. Change of Basis, DFT, and SVD. PROBABILITY: Probability. Numerical Random Variables. Markov Models. Confidence Intervals. Monte Carlo Methods. Information and Entropy. Maximum Likelihood Estimation. References. Notation. Index.

About the author

Ernest Davis is a computer science professor in the Courant Institute of Mathematical Sciences at New York University. He earned a Ph.D. in computer science from Yale University. Dr. Davis is a member of the American Association of Artificial Intelligence and is a reviewer for many journals. His research primarily focuses on spatial and physical reasoning.

Summary

Assuming as little mathematical background as possible, this classroom-tested text focuses on mathematical techniques that are most relevant to computer scientists. It covers applications from computer graphics, web search, machine learning, cryptography, and a host of other computer science areas. After an introductory chapter on MATLAB®

Product details

• Authors: Ernest Davis, Davis Ernest
• Publisher: Peters A K
• Languages: English
• Product format: Paperback / Softback
• Released: 14.10.2024
• EAN: 9781032920030
• ISBN: 978-1-0-3292003-0
• No. of pages: 431
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Miscellaneous; MATHEMATICS / General, MATHEMATICS / Applied, MATHEMATICS / Probability & Statistics / Bayesian Analysis, environmental science, engineering & technology, Probability & statistics, Probability and statistics, Environmental science, engineering and technology