Probability and Statistics for Computer Science /

This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensivebackground in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics...

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Bibliographic Details
Main Author:	Forsyth, David (Author)
Corporate Author:	SpringerLink (Online service)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2018.
Subjects:	Computer science. Computer simulation. Mathematical statistics. Probability and Statistics in Computer Science. Simulation and Modeling. Statistics and Computing/Statistics Programs. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

1 Notation and conventions
2 First Tools for Looking at Data
3 Looking at Relationships
4 Basic ideas in probability
5 Random Variables and Expectations
6 Useful Probability Distributions
7 Samples and Populations
8 The Significance of Evidence
9 Experiments
10 Inferring Probability Models from Data
11 Extracting Important Relationships in High Dimensions
12 Learning to Classify
13 Clustering: Models of High Dimensional Data
14 Regression
15 Markov Chains and Hidden Markov Models
16 Resources.