> Detail View

# Detail View ## Linear algebra and probability for computer science applications (Loan 2 times)

Material type
단행본
Personal Author
Davis, Ernest.
Title Statement
Linear algebra and probability for computer science applications / Ernest Davis.
Publication, Distribution, etc
Boca Raton, FL :   CRC Press,   c2012.
Physical Medium
xviii, 413 p. : ill. ; 25 cm.
ISBN
9781466501553 (hardback) 1466501553 (hardback)
요약
"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"--
Bibliography, Etc. Note
Includes bibliographical references and index.
Subject Added Entry-Topical Term
Computer science --Mathematics. Algebras, Linear. Probabilities.
 000 00000cam u2200205 a 4500 001 000045847276 005 20151021175534 008 151021s2012 flua b 001 0 eng d 010 ▼a 2011047969 020 ▼a 9781466501553 (hardback) 020 ▼a 1466501553 (hardback) 035 ▼a (KERIS)REF000016844428 040 ▼a DLC ▼b eng ▼c DLC ▼d YDX ▼d BTCTA ▼d UKMGB ▼d YDXCP ▼d DLC ▼d 211009 050 0 0 ▼a QA76.9.M35 ▼b D38 2012 082 0 0 ▼a 004.01/51 ▼2 23 084 ▼a 004.0151 ▼2 DDCK 090 ▼a 004.0151 ▼b D261L 100 1 ▼a Davis, Ernest. 245 1 0 ▼a Linear algebra and probability for computer science applications / ▼c Ernest Davis. 260 ▼a Boca Raton, FL : ▼b CRC Press, ▼c c2012. 300 ▼a xviii, 413 p. : ▼b ill. ; ▼c 25 cm. 504 ▼a Includes bibliographical references and index. 520 ▼a "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"-- ▼c Provided by publisher. 650 0 ▼a Computer science ▼x Mathematics. 650 0 ▼a Algebras, Linear. 650 0 ▼a Probabilities. 945 ▼a KLPA

### Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Call Number 004.0151 D261L Accession No. 121234451 Availability Available Due Date Make a Reservation Service

### Contents information

#### Table of Contents

```MATLABDesk calculator operations Booleans Nonstandard numbers Loops and conditionals Script file Functions Variable scope and parameter passing

I: Linear Algebra Vectors Definition of vectors Applications of vectorsBasic operations on vectorsDot productVectors in MATLAB: Basic operationsPlotting vectors in MATLABVectors in other programming languages

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

Vector Spaces Subspaces Coordinates, bases, linear independenceOrthogonal and orthonormal basis Operations on vector spaces Null space, image space, and rank Systems of linear equations Inverses Null space and Rank in MATLABVector spaces Linear independence and bases Sum of vector spacesOrthogonality Functions Linear transformations Inverses Systems of linear equations The general definition of vector spaces

Algorithms Gaussian elimination: Examples Gaussian elimination: DiscussionComputing a matrix inverse Inverse and systems of equations in MATLAB Ill-conditioned matrices Computational complexity

Geometry Arrows Coordinate systems Simple geometric calculationsGeometric transformations

Change of Basis, DFT, and SVD Change of coordinate systemThe formula for basis change Confusion and how to avoid it Nongeometric change of basis Color graphics Discrete Fourier transform (Optional)Singular value decompositionFurther properties of the SVDApplications of the SVDMATLAB

II: Probability Probability The interpretations of probability theory Finite sample spaces Basic combinatorial formulas The axioms of probability theoryConditional probability The likelihood interpretation Relation between likelihood and sample space probability Bayes’ law IndependenceRandom variables Application: Naive Bayes’ classification

Numerical Random Variables Marginal distribution Expected value Decision theoryVariance and standard deviation Random variables over infinite sets of integers Three important discrete distributionsContinuous random variables Two important continuous distributionsMATLAB

Markov Models Stationary probability distribution PageRank and link analysisHidden Markov models and the k-gram model

Confidence Intervals The basic formula for confidence intervals Application: Evaluating a classifier Bayesian statistical inference (Optional) Confidence intervals in the frequentist viewpoint: (Optional) Hypothesis testing and statistical significance Statistical inference and ESP

Monte Carlo Methods Finding area Generating distributions Counting Counting solutions to DNF (Optional) Sums, expected values, integrals Probabilistic problems Resampling Pseudo-random numbers Other probabilistic algorithmsMATLAB

Information and Entropy Information Entropy Conditional entropy and mutual information Coding Entropy of numeric and continuous random variables The principle of maximum entropyStatistical inference

Maximum Likelihood Estimation Sampling Uniform distribution Gaussian distribution: Known variance Gaussian distribution: Unknown variance Least squares estimates Principal component analysis Applications of PCA

References
Notation
Index```

Information Provided By: : ### New Arrivals Books in Related Fields

#### 디지털·미디어 리터러시 수업 : 블로그·팟캐스트·사진·인포그래픽·브이로그·영상·애니메이션·리믹스·소셜미디어 만들며 배우기

Hobbs, Renee (2021)

#### Cloud ethics : algorithms and the attributes of ourselves and others

Amoore, Louise (2020)

#### 비트의 세계 : 프로그래머의 눈으로 본 세상, 인간, 코드

Auerbach, David (2021)

김자미 (2021)

김자미 (2021)

#### 클라우드 핀옵스 : 비용은 최소화 운영은 최적화

Storment, J. R (2020)

#### Cracking the digital ceiling : women in computing around the world

Frieze, Carol (2020)

함윤식 (2021)

#### 이더리움 디앱 개발 : 스마트 컨트랙트에서 투표 디앱까지 실습하며 배우는 이더리움 디앱

Infante, Roberto (2020)

앤미디어 (2020)

#### IT 좀 아는 사람 : 비전공자도 IT 전문가처럼 생각하는 법

Mehta, Neel (2021)

#### 디자인 협업 : 함께 더 나은 제품을 만드는 경험

Govella, Austin (2021)

강상진 (2020)

#### Internet of things (IOT) applications for enterprise productivity

Koç, Erdinç (2020)

#### Applications of emerging memory technology : beyond storage

Suri, Manan (2020)

#### IoT machine learning applications in telecom, energy, and agriculture : with Raspberry Pi and Arduino using Python

Mathur, Puneet (2020)

#### Cloud computing and services science : 9th International Conference, CLOSER 2019, Heraklion, Crete, Greece, May 2-4, 2019, Revised Selected Papers

International Conference on Cloud Computing and Services Science (2020)

#### Programming persistent memory : a comprehensive guide for developers

Scargall, Steve (2020)