A K Peters/CRC Press
Based on the author's course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the chapters discuss relevant MATLAB functi
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.