ABSTRACT

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

chapter 1|14 pages

MATLAB

part I|2 pages

I Linear Algebra

chapter 2|30 pages

Vectors

chapter 3|34 pages

Matrices

chapter 4|34 pages

Vector Spaces

chapter 5|28 pages

Algorithms

chapter 6|38 pages

Geometry

chapter 7|40 pages

Change of Basis, DFT, and SVD

part II|2 pages

II Probability

chapter 8|34 pages

Probability

chapter 9|42 pages

Numerical Random Variables

chapter 10|24 pages

Markov Models

chapter 11|16 pages

Confidence Intervals

chapter 12|20 pages

Monte Carlo Methods

chapter 13|24 pages

Information and Entropy

chapter 14|18 pages

Maximum Likelihood Estimation