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عنوان
Linear algebra and probability for computer science applications /

پدید آورنده
Ernest Davis

موضوع
Algebras, Linear,Computer science-- Mathematics,Probabilities

رده
QA76
.
9
.
M35
D38
2012

کتابخانه
Center and Library of Islamic Studies in European Languages

محل استقرار
استان: Qom ـ شهر: Qom

Center and Library of Islamic Studies in European Languages

تماس با کتابخانه : 32910706-025

INTERNATIONAL STANDARD BOOK NUMBER

(Number (ISBN
1466501553
(Number (ISBN
9781466501553

NATIONAL BIBLIOGRAPHY NUMBER

Number
dltt

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
Linear algebra and probability for computer science applications /
General Material Designation
[Book]
First Statement of Responsibility
Ernest Davis

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
xviii, 413 pages :
Other Physical Details
illustrations ;
Dimensions
25 cm

INTERNAL BIBLIOGRAPHIES/INDEXES NOTE

Text of Note
Includes bibliographical references and index

CONTENTS NOTE

Text of Note
1. MATLAB -- Desk calculator operations -- Booleans -- Nonstandard numbers -- Loops and conditionals -- Script file -- Functions -- Variable scope and parameter passing -- Part 1. Linear algebra -- 2. Vectors -- Definition of vectors -- Applications of vectors -- Basic operations on vectors -- Dot product -- Vectors in MATLAB basic operations -- Plotting vectors in MATLAB -- Vectors in other programming languages -- 3. Matrices -- Definition of matrices -- Applications of matrices -- Simple operations on matrices -- Multiplying a matrix times a vector -- Linear transformation -- Systems of linear equations -- Matrix multiplication -- Vectors as matrices -- Algebraic properties of matrix multiplication -- Matrices in MATLAB -- 4. Vector spaces -- Fundamentals of vector spaces -- Proofs and other abstract mathematics (optional) -- Vector spaces in general (very optional) -- 5. Algorithms -- Gaussian elimination : examples -- Gaussian elimination : discussion -- Computing a matrix inverse -- Inverse and systems of equations in MATLAB -- Ill-conditioned matrices -- Computational complexity -- 6. Geometry -- Arrows -- Coordinate systems -- Simple geometric calculations -- Geometric transformations -- 7. Change of basis, DFT, and SVD -- Change of coordinate system -- The formula for basis change -- Confusion and how to avoid it -- Nongeometric change of basis -- Color graphics -- Discrete Fourier transform (optional) -- Singular value decomposition -- Further properties of the SVD -- Applications of the SVD -- MATLAB --
Text of Note
Part 2. Probability -- 8. Probability -- The interpretation of probability theory -- Finite sample spaces -- Basic combinatorial formulas -- The axioms of probability theory -- Conditional probability -- The likelihood interpretation -- Relation between likelihood and sample probability -- Bayes' law -- Independence -- Random variables -- Application : naive Bayes classification -- 9. Numerical random variables -- Marginal distribution -- Expected value -- Decision theory -- Variance and standard deviation -- Random variables over infinite sets of integers -- Three important discrete distributions -- Continuous random variables -- Two important continuous distributions -- 10. Markov models -- Stationary probability distribution -- PageRank and link analysis -- Hidden Markov models and the K-gram model -- 11. Confidence intervals -- The basic formula for confidence intervals -- Application : evaluating a classifier -- Bayesian statistcial inference (optional) -- Confidence intervals in the frequentist viewpoint (optional) -- Hypothesis testing and statistical significance -- Statistical inference and ESP -- 12. Monte Carlo methods -- Finding area -- Generating distributions -- Counting -- Counting solutions to a DNF formula (optional) -- Sums, expected values, and integrals -- Probabilistic problems -- Resampling -- Pseudorandom numbers -- Other probabilistic algorithms -- MATLAB -- 13. Informational and entropy -- Information -- Entropy -- Conditional entropy and mutual information -- Coding -- Entropy of numeric and continuous random variables -- The principle of maximum entropy -- 14. Maximum likelihood estimation -- Sampling -- Uniform distribution -- Gaussian distribution : known variance -- Gaussian distribution : unknown variance -- Least squares estimates -- Principal component analysis -- Applications of principal component analysis
00
00

SUMMARY OR ABSTRACT

Text of Note
"Taking a computer scientist's point of view, this classroom-tested text gives an introduction to linear algebra and probability theory, including some basic aspects of statistics. It discusses examples of applications from a wide range of areas of computer science, including computer graphics, computer vision, robotics, natural language processing, web search, machine learning, statistical analysis, game playing, graph theory, scientific computing, decision theory, coding, cryptography, network analysis, data compression, and signal processing. It includes an extensive discussion of MATLAB, and includes numerous MATLAB exercises and programming assignments"--

TOPICAL NAME USED AS SUBJECT

Algebras, Linear
Computer science-- Mathematics
Probabilities

DEWEY DECIMAL CLASSIFICATION

Number
004
.
01/51
Edition
23

LIBRARY OF CONGRESS CLASSIFICATION

Class number
QA76
.
9
.
M35
Book number
D38
2012

PERSONAL NAME - PRIMARY RESPONSIBILITY

Davis, Ernest

ORIGINATING SOURCE

Date of Transaction
20120717114415.0

ELECTRONIC LOCATION AND ACCESS

Electronic name
 مطالعه متن کتاب 

[Book]

Y

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