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

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assignments/python_lab1.pdf460.87kB
assignments/python_lab2.pdf127.41kB
assignments/python_lab3.pdf136.48kB
assignments/python_lab4.pdf142.70kB
assignments/python_lab5.pdf198.59kB
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assignments/README.txt0.27kB
lectures/tuts/Coding the Matrix Linear Algebra through Computer Science Applications 8.0 How to submit assignments.mp49.20MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.0 Course Introduction Part 1 (953).mp4130.04MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.1 Course Introduction Part 2 (849).mp490.84MB
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).mp4148.30MB
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).mp436.54MB
lectures/week0-the-function-and-the-field/Coding the Matrix Linear Algebra through Computer Science Applications 0.4 The Field Playing with C (1519).mp492.15MB
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).mp471.38MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.0 The Vector What is a vector (820).mp451.36MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.1 The Vector Vector addition and scalar-vector multiplication (1016).mp463.58MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.2 The Vector Dictionary-based representations of vectors (910).mp457.62MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.3 The Vector Vectors over GF(2) (918).mp456.72MB
lectures/week1-the-vector/Coding the Matrix Linear Algebra through Computer Science Applications 1.4 The Vector Dot-product (849).mp454.09MB
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).mp413.55MB
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).mp410.02MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.0 The Vector Space Linear combinations.mp429.36MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.1 The Vector Space Span.mp422.53MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.2 The Vector Space Geometry of Sets of Vectors.mp480.21MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.3 The Vector Space Vector spaces.mp432.25MB
lectures/week2-the-vector-space/Coding the Matrix Linear Algebra through Computer Science Applications 2.4 The Vector Space Checksum function.mp410.35MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.0 The Matrix What is a matrix.mp485.38MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.1 The Matrix Matrix-vector and vector-matrix multiplication.mp433.58MB
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.mp432.95MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.3 The Matrix Null space.mp411.17MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.4 The Matrix Error-correcting codes.mp414.43MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.5 The Matrix Matrices and their functions.mp459.52MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.6 The Matrix Linear functions.mp489.87MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.7 The Matrix Matrix-matrix multiplication.mp470.58MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.8 The Matrix Matrix-matrix multiplication and function composition.mp419.35MB
lectures/week3-the-matrix/Coding the Matrix Linear Algebra through Computer Science Applications 3.9 The Matrix Matrix inverse.mp477.70MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.0 The Basis Coordinate systems.mp410.91MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.1 The Basis Lossy compression.mp411.46MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.10 The Basis The Exchange Lemma.mp428.07MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.2 The Basis Algorithms for finding a set of generators.mp412.90MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.3 The Basis Minimum spanning forest.mp475.45MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.4 The Basis Linear dependence.mp4107.27MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.5 The Basis Basis.mp424.20MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.6 The Basis Unique representation.mp47.18MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.7 The Basis Change of basis.mp414.49MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.8 The Basis Perspective rendering.mp432.91MB
lectures/week4-the-basis/Coding the Matrix Linear Algebra through Computer Science Applications 4.9 The Basis Perspective rectification.mp466.15MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.0 Dimension The size of a basis.mp436.20MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.1 Dimension Dimension and rank I.mp418.66MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.2 Dimension Dimension and rank II.mp4109.94MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.3 Dimension Direct sum.mp430.73MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.4 Dimension Dimension and linear functions I.mp446.62MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.5 Dimension Dimension and linear functions II.mp429.88MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.6 Dimension Two representations of vector spaces.mp439.60MB
lectures/week5-dimension/Coding the Matrix Linear Algebra through Computer Science Applications 5.7 Dimension Threshold secret sharing.mp424.70MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.0 Gaussian Elimination Echelon form.mp416.11MB
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.mp437.83MB
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.mp435.68MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.3 Gaussian Elimination Factoring integers.mp4113.64MB
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.mp418.61MB
lectures/week6-gaussian-elimination-and-the-inner-product/Coding the Matrix Linear Algebra through Computer Science Applications 6.5 The Inner Product Orthogonality.mp4106.68MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.0 Orthogonalization Finding the closest point in a plane.mp415.47MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.1 Orthogonalization Projection orthogonal to multiple vectors.mp4122.65MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.2 Orthogonalization Building an orthogonal set of generators.mp441.60MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.3 Orthogonalization Computing a basis.mp427.63MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.4 Orthogonalization Orthogonal complement.mp437.25MB
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.mp420.58MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.6 Orthogonalization The QR factorization.mp420.44MB
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.mp441.83MB
lectures/week7-orthogonalization/Coding the Matrix Linear Algebra through Computer Science Applications 7.8 Orthogonalization Applications of least squares.mp434.02MB
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