[Coursera] Coding the Matrix: Linear Algebra through Computer Science Applications
Philip Klein (Brown University)

coursera-coding-the-matrix (73 files)
assignments/python_lab1.pdf 460.87kB
assignments/python_lab2.pdf 127.41kB
assignments/python_lab3.pdf 136.48kB
assignments/python_lab4.pdf 142.70kB
assignments/python_lab5.pdf 198.59kB
assignments/python_lab6.pdf 165.62kB
assignments/python_lab7.pdf 166.02kB
assignments/python_lab8.pdf 4.82MB
assignments/python_lab9.pdf 193.57kB
assignments/README.txt 0.27kB
lectures/tuts/Coding the Matrix Linear Algebra through Computer Science Applications 8.0 How to submit assignments.mp4 9.20MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.0 Course Introduction Part 1 (953).mp4 130.04MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.1 Course Introduction Part 2 (849).mp4 90.84MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.2 The Function The function and other preliminaries (2055).mp4 148.30MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.3 The Field Introduction to complex numbers (552).mp4 36.54MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.4 The Field Playing with C (1519).mp4 92.15MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.5 The Field Playing with GF(2) (1028).mp4 71.38MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.0 The Vector What is a vector (820).mp4 51.36MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.1 The Vector Vector addition and scalar-vector multiplication (1016).mp4 63.58MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.2 The Vector Dictionary-based representations of vectors (910).mp4 57.62MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.3 The Vector Vectors over GF(2) (918).mp4 56.72MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.4 The Vector Dot-product (849).mp4 54.09MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.5 The Vector Dot-product of vectors over GF(2) (444).mp4 13.55MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.6 The Vector Solving a triangular system of linear equations (400).mp4 10.02MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.0 The Vector Space Linear combinations.mp4 29.36MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.1 The Vector Space Span.mp4 22.53MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.2 The Vector Space Geometry of Sets of Vectors.mp4 80.21MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.3 The Vector Space Vector spaces.mp4 32.25MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.4 The Vector Space Checksum function.mp4 10.35MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.0 The Matrix What is a matrix.mp4 85.38MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.1 The Matrix Matrix-vector and vector-matrix multiplication.mp4 33.58MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.2 The Matrix Matrix-vector multiplication in terms of dot-products.mp4 32.95MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.3 The Matrix Null space.mp4 11.17MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.4 The Matrix Error-correcting codes.mp4 14.43MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.5 The Matrix Matrices and their functions.mp4 59.52MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.6 The Matrix Linear functions.mp4 89.87MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.7 The Matrix Matrix-matrix multiplication.mp4 70.58MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.8 The Matrix Matrix-matrix multiplication and function composition.mp4 19.35MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.9 The Matrix Matrix inverse.mp4 77.70MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.0 The Basis Coordinate systems.mp4 10.91MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.1 The Basis Lossy compression.mp4 11.46MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.10 The Basis The Exchange Lemma.mp4 28.07MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.2 The Basis Algorithms for finding a set of generators.mp4 12.90MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.3 The Basis Minimum spanning forest.mp4 75.45MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.4 The Basis Linear dependence.mp4 107.27MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.5 The Basis Basis.mp4 24.20MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.6 The Basis Unique representation.mp4 7.18MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.7 The Basis Change of basis.mp4 14.49MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.8 The Basis Perspective rendering.mp4 32.91MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.9 The Basis Perspective rectification.mp4 66.15MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.0 Dimension The size of a basis.mp4 36.20MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.1 Dimension Dimension and rank I.mp4 18.66MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.2 Dimension Dimension and rank II.mp4 109.94MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.3 Dimension Direct sum.mp4 30.73MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.4 Dimension Dimension and linear functions I.mp4 46.62MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.5 Dimension Dimension and linear functions II.mp4 29.88MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.6 Dimension Two representations of vector spaces.mp4 39.60MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.7 Dimension Threshold secret sharing.mp4 24.70MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.0 Gaussian Elimination Echelon form.mp4 16.11MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.1 Gaussian Elimination Transforming a matrix to echelon form.mp4 37.83MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.2 Gaussian Elimination Using Gaussian elimination to solve a system of equations.mp4 35.68MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.3 Gaussian Elimination Factoring integers.mp4 113.64MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.4 The Inner Product The inner product.mp4 18.61MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.5 The Inner Product Orthogonality.mp4 106.68MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.0 Orthogonalization Finding the closest point in a plane.mp4 15.47MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.1 Orthogonalization Projection orthogonal to multiple vectors.mp4 122.65MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.2 Orthogonalization Building an orthogonal set of generators.mp4 41.60MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.3 Orthogonalization Computing a basis.mp4 27.63MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.4 Orthogonalization Orthogonal complement.mp4 37.25MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.5 Orthogonalization Two ways to find a basis for the null space.mp4 20.58MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.6 Orthogonalization The QR factorization.mp4 20.44MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.7 Orthogonalization Using the QR factorization to solve a matrix equation Ax = b.mp4 41.83MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.8 Orthogonalization Applications of least squares.mp4 34.02MB
Type: Course
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Bibtex:
@article{,
title= {[Coursera] Coding the Matrix: Linear Algebra through Computer Science Applications},
keywords= {},
journal= {},
author= {Philip Klein (Brown University)},
year= {2015},
url= {},
license= {},
abstract= {When you take a digital photo with your phone or transform the image in Photoshop, when you play a video game or watch a movie with digital effects, when you do a web search or make a phone call, you are using technologies that build upon linear algebra. Linear algebra provides concepts that are crucial to many areas of computer science, including graphics, image processing, cryptography, machine learning, computer vision, optimization, graph algorithms, quantum computation, computational biology, information retrieval and web search. Linear algebra in turn is built on two basic elements, the matrix and the vector.

In this class, you will learn the concepts and methods of linear algebra, and how to use them to think about problems arising in computer science. You will write small programs in the programming language Python to implement basic matrix and vector functionality and algorithms, and use these to process real-world data to achieve such tasks as: two-dimensional graphics transformations, face morphing, face detection, image transformations such as blurring and edge detection, image perspective removal, audio and image compression, searching within an image or an audio clip, classification of tumors as malignant or benign, integer factorization, error-correcting codes, secret-sharing, network layout, document classification, and computing Pagerank (Google's ranking method).},
superseded= {},
terms= {}
}


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