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[] Udemy - Complete linear algebra theory and implementation

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文件列表

  1. 11. Least-squares for model-fitting in statistics/8. Least-squares application 2.mp4 133MB
  2. 14. Quadratic form and definiteness/7. Application of the normalized quadratic form PCA.mp4 131MB
  3. 13. Singular value decomposition/5. Spectral theory of matrices.mp4 117MB
  4. 11. Least-squares for model-fitting in statistics/2. Introduction to least-squares.mp4 107MB
  5. 7. Solving systems of equations/2. Systems of equations algebra and geometry.mp4 100MB
  6. 12. Eigendecomposition/10. Matrix powers via diagonalization.mp4 100MB
  7. 5. Matrix rank/4. Computing rank theory and practice.mp4 90MB
  8. 6. Matrix spaces/2. Column space of a matrix.mp4 86MB
  9. 9. Matrix inverse/5. Computing the inverse via row reduction.mp4 86MB
  10. 12. Eigendecomposition/2. What are eigenvalues and eigenvectors.mp4 86MB
  11. 11. Least-squares for model-fitting in statistics/7. Least-squares application 1.mp4 81MB
  12. 14. Quadratic form and definiteness/5. Code challenge Visualize the normalized quadratic form.mp4 81MB
  13. 13. Singular value decomposition/3. Code challenge SVD vs. eigendecomposition for square symmetric matrices.mp4 79MB
  14. 13. Singular value decomposition/10. Code challenge Create matrix with desired condition number.mp4 79MB
  15. 2. Vectors/9. Dot product geometry sign and orthogonality.mp4 77MB
  16. 9. Matrix inverse/7. Left inverse and right inverse.mp4 77MB
  17. 4. Matrix multiplications/7. Matrix-vector multiplication.mp4 76MB
  18. 2. Vectors/26. Linear independence.mp4 76MB
  19. 10. Projections and orthogonalization/3. Projections in R^N.mp4 76MB
  20. 13. Singular value decomposition/2. Singular value decomposition (SVD).mp4 74MB
  21. 12. Eigendecomposition/13. Eigendecomposition of symmetric matrices.mp4 74MB
  22. 12. Eigendecomposition/3. Finding eigenvalues.mp4 73MB
  23. 13. Singular value decomposition/7. Convert singular values to percent variance.mp4 73MB
  24. 2. Vectors/22. Subspaces.mp4 70MB
  25. 13. Singular value decomposition/6. SVD for low-rank approximations.mp4 68MB
  26. 10. Projections and orthogonalization/7. Gram-Schmidt and QR decomposition.mp4 68MB
  27. 14. Quadratic form and definiteness/2. The quadratic form in algebra.mp4 66MB
  28. 14. Quadratic form and definiteness/8. Quadratic form of generalized eigendecomposition.mp4 65MB
  29. 4. Matrix multiplications/10. Code challenge Pure and impure rotation matrices.mp4 65MB
  30. 1. Introductions/1. What is linear algebra.mp4 65MB
  31. 12. Eigendecomposition/7. Finding eigenvectors.mp4 65MB
  32. 12. Eigendecomposition/12. Eigenvectors of repeated eigenvalues.mp4 65MB
  33. 14. Quadratic form and definiteness/3. The quadratic form in geometry.mp4 65MB
  34. 6. Matrix spaces/4. Null space and left null space of a matrix.mp4 64MB
  35. 5. Matrix rank/2. Rank concepts, terms, and applications.mp4 63MB
  36. 8. Matrix determinant/6. Code challenge determinant of shifted matrices.mp4 62MB
  37. 12. Eigendecomposition/16. Generalized eigendecomposition.mp4 62MB
  38. 7. Solving systems of equations/4. Gaussian elimination.mp4 62MB
  39. 7. Solving systems of equations/6. Reduced row echelon form.mp4 61MB
  40. 2. Vectors/24. Span.mp4 60MB
  41. 5. Matrix rank/11. Making a matrix full-rank by shifting.mp4 60MB
  42. 5. Matrix rank/5. Rank of added and multiplied matrices.mp4 59MB
  43. 9. Matrix inverse/9. Pseudo-inverse, part 1.mp4 56MB
  44. 12. Eigendecomposition/11. Eigenvectors of distinct eigenvalues.mp4 56MB
  45. 5. Matrix rank/7. Code challenge scalar multiplication and rank.mp4 56MB
  46. 2. Vectors/18. Hermitian transpose (a.k.a. conjugate transpose).mp4 55MB
  47. 10. Projections and orthogonalization/6. Orthogonal matrices.mp4 55MB
  48. 3. Introduction to matrices/4. A zoo of matrices.mp4 55MB
  49. 4. Matrix multiplications/12. Additive and multiplicative symmetric matrices.mp4 54MB
  50. 9. Matrix inverse/2. Matrix inverse Concept and applications.mp4 54MB
  51. 14. Quadratic form and definiteness/9. Matrix definiteness, geometry, and eigenvalues.mp4 53MB
  52. 13. Singular value decomposition/9. Condition number of a matrix.mp4 53MB
  53. 4. Matrix multiplications/9. 2D transformation matrices.mp4 52MB
  54. 9. Matrix inverse/4. The MCA algorithm to compute the inverse.mp4 52MB
  55. 10. Projections and orthogonalization/2. Projections in R^2.mp4 52MB
  56. 12. Eigendecomposition/8. Eigendecomposition by hand two examples.mp4 52MB
  57. 8. Matrix determinant/5. Determinant of a 3x3 matrix.mp4 52MB
  58. 2. Vectors/27. Basis.mp4 51MB
  59. 6. Matrix spaces/7. Example of the four subspaces.mp4 50MB
  60. 13. Singular value decomposition/8. SVD, matrix inverse, and pseudoinverse.mp4 50MB
  61. 4. Matrix multiplications/16. Multiplication of two symmetric matrices.mp4 50MB
  62. 11. Least-squares for model-fitting in statistics/3. Least-squares via left inverse.mp4 49MB
  63. 8. Matrix determinant/2. Determinant concept and applications.mp4 48MB
  64. 2. Vectors/2. Algebraic and geometric interpretations of vectors.mp4 48MB
  65. 10. Projections and orthogonalization/9. Code challenge Inverse via QR.mp4 48MB
  66. 10. Projections and orthogonalization/5. Code challenge decompose vector to orthogonal components.mp4 48MB
  67. 10. Projections and orthogonalization/4. Orthogonal and parallel vector components.mp4 47MB
  68. 12. Eigendecomposition/9. Diagonalization.mp4 47MB
  69. 11. Least-squares for model-fitting in statistics/5. Least-squares via row-reduction.mp4 47MB
  70. 4. Matrix multiplications/2. Introduction to standard matrix multiplication.mp4 45MB
  71. 14. Quadratic form and definiteness/6. Eigenvectors and the quadratic form surface.mp4 45MB
  72. 4. Matrix multiplications/18. Frobenius dot product.mp4 45MB
  73. 5. Matrix rank/9. Rank of A^TA and AA^T.mp4 45MB
  74. 2. Vectors/20. Code challenge dot products with unit vectors.mp4 45MB
  75. 2. Vectors/12. Code challenge dot product sign and scalar multiplication.mp4 45MB
  76. 2. Vectors/16. Vector cross product.mp4 44MB
  77. 2. Vectors/15. Outer product.mp4 42MB
  78. 3. Introduction to matrices/2. Matrix terminology and dimensionality.mp4 41MB
  79. 12. Eigendecomposition/6. Code challenge eigenvalues of random matrices.mp4 40MB
  80. 7. Solving systems of equations/8. Matrix spaces after row reduction.mp4 40MB
  81. 7. Solving systems of equations/7. Code challenge RREF of matrices with different sizes and ranks.mp4 39MB
  82. 2. Vectors/21. Dimensions and fields in linear algebra.mp4 39MB
  83. 4. Matrix multiplications/3. Four ways to think about matrix multiplication.mp4 38MB
  84. 13. Singular value decomposition/4. SVD and the four subspaces.mp4 38MB
  85. 9. Matrix inverse/6. Code challenge inverse of a diagonal matrix.mp4 37MB
  86. 4. Matrix multiplications/6. Order-of-operations on matrices.mp4 37MB
  87. 3. Introduction to matrices/13. Code challenge linearity of trace.mp4 36MB
  88. 4. Matrix multiplications/4. Code challenge matrix multiplication by layering.mp4 36MB
  89. 11. Least-squares for model-fitting in statistics/4. Least-squares via orthogonal projection.mp4 35MB
  90. 5. Matrix rank/8. Code challenge reduced-rank matrix via multiplication.mp4 34MB
  91. 4. Matrix multiplications/15. Code challenge symmetry of combined symmetric matrices.mp4 34MB
  92. 2. Vectors/17. Vectors with complex numbers.mp4 33MB
  93. 2. Vectors/5. Vector-vector multiplication the dot product.mp4 32MB
  94. 14. Quadratic form and definiteness/4. The normalized quadratic form.mp4 32MB
  95. 14. Quadratic form and definiteness/10. Proof A^TA is always positive (semi)definite.mp4 31MB
  96. 3. Introduction to matrices/9. Transpose.mp4 31MB
  97. 6. Matrix spaces/5. Columnleft-null and rownull spaces are orthogonal.mp4 31MB
  98. 11. Least-squares for model-fitting in statistics/6. Model-predicted values and residuals.mp4 31MB
  99. 5. Matrix rank/10. Code challenge rank of multiplied and summed matrices.mp4 30MB
  100. 1. Introductions/2. Linear algebra applications.mp4 30MB
  101. 7. Solving systems of equations/3. Converting systems of equations to matrix equations.mp4 29MB
  102. 2. Vectors/4. Vector-scalar multiplication.mp4 29MB
  103. 2. Vectors/23. Subspaces vs. subsets.mp4 29MB
  104. 6. Matrix spaces/8. More on Ax=b and Ax=0.mp4 28MB
  105. 2. Vectors/13. Code challenge is the dot product commutative.mp4 28MB
  106. 8. Matrix determinant/4. Determinant of a 2x2 matrix.mp4 27MB
  107. 3. Introduction to matrices/12. Diagonal and trace.mp4 27MB
  108. 3. Introduction to matrices/6. Matrix addition and subtraction.mp4 27MB
  109. 1. Introductions/3. How best to learn from this course.mp4 27MB
  110. 6. Matrix spaces/6. Dimensions of columnrownull spaces.mp4 27MB
  111. 9. Matrix inverse/3. Inverse of a 2x2 matrix.mp4 27MB
  112. 2. Vectors/19. Interpreting and creating unit vectors.mp4 27MB
  113. 7. Solving systems of equations/5. Echelon form and pivots.mp4 26MB
  114. 2. Vectors/3. Vector addition and subtraction.mp4 26MB
  115. 12. Eigendecomposition/5. Code challenge eigenvalues of diagonal and triangular matrices.mp4 26MB
  116. 3. Introduction to matrices/8. Code challenge is matrix-scalar multiplication a linear operation.mp4 25MB
  117. 4. Matrix multiplications/11. Additive and multiplicative matrix identities.mp4 25MB
  118. 8. Matrix determinant/3. Code challenge determinant of small and large singular matrices.mp4 25MB
  119. 5. Matrix rank/12. Code challenge is this vector in the span of this set.mp4 24MB
  120. 12. Eigendecomposition/15. Code challenge trace and determinant, eigenvalues sum and product.mp4 24MB
  121. 2. Vectors/7. Vector length.mp4 24MB
  122. 2. Vectors/6. Code challenge dot products with matrix columns.mp4 23MB
  123. 1. Introductions/4. Using MATLAB, Octave, or Python in this course.mp4 21MB
  124. 8. Matrix determinant/7. Find matrix values for a given determinant.mp4 21MB
  125. 4. Matrix multiplications/17. Code challenge standard and Hadamard multiplication for diagonal matrices.mp4 20MB
  126. 6. Matrix spaces/3. Row space of a matrix.mp4 19MB
  127. 4. Matrix multiplications/5. Matrix multiplication with a diagonal matrix.mp4 19MB
  128. 1. Introductions/5. Leaving reviews, course coupons.mp4 18MB
  129. 12. Eigendecomposition/14. Eigendecomposition of singular matrices.mp4 16MB
  130. 4. Matrix multiplications/19. What about matrix division.mp4 14MB
  131. 9. Matrix inverse/8. Proof the inverse is unique.mp4 14MB
  132. 10. Projections and orthogonalization/8. Matrix inverse via QR decomposition.mp4 13MB
  133. 9. Matrix inverse/10. Code challenge pseudoinverse of invertible matrices.mp4 13MB
  134. 2. Vectors/14. Vector Hadamard multiplication.mp4 12MB
  135. 4. Matrix multiplications/13. Hadamard (element-wise) multiplication.mp4 12MB
  136. 12. Eigendecomposition/4. Shortcut for eigenvalues of a 2x2 matrix.mp4 9MB
  137. 3. Introduction to matrices/7. Matrix-scalar multiplication.mp4 8MB
  138. 3. Introduction to matrices/10. Complex matrices.mp4 7MB
  139. 2. Vectors/1.1 linalg_vectors.zip.zip 385KB
  140. 13. Singular value decomposition/1.1 linalg_svd.zip.zip 331KB
  141. 11. Least-squares for model-fitting in statistics/1.1 linalg_leastsquares.zip.zip 315KB
  142. 12. Eigendecomposition/1.1 linalg_eig.zip.zip 303KB
  143. 10. Projections and orthogonalization/1.1 linalg_projorth.zip.zip 288KB
  144. 14. Quadratic form and definiteness/1.1 linalg_quadformDefinite.zip.zip 264KB
  145. 9. Matrix inverse/1.1 linalg_inverse.zip.zip 226KB
  146. 4. Matrix multiplications/1.1 linalg_matrixMult.zip.zip 215KB
  147. 7. Solving systems of equations/1.1 linalg_systems.zip.zip 211KB
  148. 6. Matrix spaces/1.1 linalg_matrixSpaces.zip.zip 210KB
  149. 5. Matrix rank/1.1 linalg_matrixRank.zip.zip 180KB
  150. 3. Introduction to matrices/1.1 linalg_matrices.zip.zip 166KB
  151. 8. Matrix determinant/1.1 linalg_matrixDet.pdf.pdf 138KB
  152. 11. Least-squares for model-fitting in statistics/8. Least-squares application 2.srt 23KB
  153. 9. Matrix inverse/5. Computing the inverse via row reduction.srt 22KB
  154. 5. Matrix rank/4. Computing rank theory and practice.srt 21KB
  155. 14. Quadratic form and definiteness/7. Application of the normalized quadratic form PCA.srt 20KB
  156. 11. Least-squares for model-fitting in statistics/8. Least-squares application 2.vtt 20KB
  157. 12. Eigendecomposition/10. Matrix powers via diagonalization.srt 20KB
  158. 6. Matrix spaces/2. Column space of a matrix.srt 20KB
  159. 10. Projections and orthogonalization/7. Gram-Schmidt and QR decomposition.srt 20KB
  160. 2. Vectors/9. Dot product geometry sign and orthogonality.srt 20KB
  161. 12. Eigendecomposition/3. Finding eigenvalues.srt 19KB
  162. 2. Vectors/26. Linear independence.srt 19KB
  163. 9. Matrix inverse/5. Computing the inverse via row reduction.vtt 19KB
  164. 2. Vectors/22. Subspaces.srt 19KB
  165. 4. Matrix multiplications/7. Matrix-vector multiplication.srt 19KB
  166. 7. Solving systems of equations/2. Systems of equations algebra and geometry.srt 19KB
  167. 5. Matrix rank/4. Computing rank theory and practice.vtt 18KB
  168. 12. Eigendecomposition/13. Eigendecomposition of symmetric matrices.srt 18KB
  169. 14. Quadratic form and definiteness/7. Application of the normalized quadratic form PCA.vtt 18KB
  170. 10. Projections and orthogonalization/3. Projections in R^N.srt 18KB
  171. 12. Eigendecomposition/10. Matrix powers via diagonalization.vtt 17KB
  172. 6. Matrix spaces/2. Column space of a matrix.vtt 17KB
  173. 2. Vectors/9. Dot product geometry sign and orthogonality.vtt 17KB
  174. 7. Solving systems of equations/6. Reduced row echelon form.srt 17KB
  175. 10. Projections and orthogonalization/7. Gram-Schmidt and QR decomposition.vtt 17KB
  176. 9. Matrix inverse/7. Left inverse and right inverse.srt 17KB
  177. 12. Eigendecomposition/2. What are eigenvalues and eigenvectors.srt 17KB
  178. 10. Projections and orthogonalization/6. Orthogonal matrices.srt 17KB
  179. 2. Vectors/26. Linear independence.vtt 17KB
  180. 12. Eigendecomposition/3. Finding eigenvalues.vtt 17KB
  181. 6. Matrix spaces/4. Null space and left null space of a matrix.srt 17KB
  182. 5. Matrix rank/7. Code challenge scalar multiplication and rank.srt 17KB
  183. 11. Least-squares for model-fitting in statistics/2. Introduction to least-squares.srt 17KB
  184. 4. Matrix multiplications/7. Matrix-vector multiplication.vtt 16KB
  185. 2. Vectors/22. Subspaces.vtt 16KB
  186. 7. Solving systems of equations/2. Systems of equations algebra and geometry.vtt 16KB
  187. 8. Matrix determinant/6. Code challenge determinant of shifted matrices.srt 16KB
  188. 12. Eigendecomposition/13. Eigendecomposition of symmetric matrices.vtt 16KB
  189. 13. Singular value decomposition/3. Code challenge SVD vs. eigendecomposition for square symmetric matrices.srt 16KB
  190. 13. Singular value decomposition/2. Singular value decomposition (SVD).srt 16KB
  191. 10. Projections and orthogonalization/3. Projections in R^N.vtt 15KB
  192. 7. Solving systems of equations/4. Gaussian elimination.srt 15KB
  193. 13. Singular value decomposition/5. Spectral theory of matrices.srt 15KB
  194. 7. Solving systems of equations/6. Reduced row echelon form.vtt 15KB
  195. 12. Eigendecomposition/7. Finding eigenvectors.srt 15KB
  196. 11. Least-squares for model-fitting in statistics/7. Least-squares application 1.srt 15KB
  197. 2. Vectors/18. Hermitian transpose (a.k.a. conjugate transpose).srt 15KB
  198. 12. Eigendecomposition/2. What are eigenvalues and eigenvectors.vtt 15KB
  199. 10. Projections and orthogonalization/6. Orthogonal matrices.vtt 15KB
  200. 9. Matrix inverse/2. Matrix inverse Concept and applications.srt 15KB
  201. 9. Matrix inverse/7. Left inverse and right inverse.vtt 15KB
  202. 12. Eigendecomposition/12. Eigenvectors of repeated eigenvalues.srt 15KB
  203. 6. Matrix spaces/4. Null space and left null space of a matrix.vtt 15KB
  204. 14. Quadratic form and definiteness/2. The quadratic form in algebra.srt 15KB
  205. 14. Quadratic form and definiteness/3. The quadratic form in geometry.srt 15KB
  206. 4. Matrix multiplications/9. 2D transformation matrices.srt 15KB
  207. 13. Singular value decomposition/10. Code challenge Create matrix with desired condition number.srt 15KB
  208. 13. Singular value decomposition/7. Convert singular values to percent variance.srt 15KB
  209. 4. Matrix multiplications/12. Additive and multiplicative symmetric matrices.srt 15KB
  210. 11. Least-squares for model-fitting in statistics/2. Introduction to least-squares.vtt 15KB
  211. 2. Vectors/12. Code challenge dot product sign and scalar multiplication.srt 14KB
  212. 5. Matrix rank/7. Code challenge scalar multiplication and rank.vtt 14KB
  213. 8. Matrix determinant/5. Determinant of a 3x3 matrix.srt 14KB
  214. 10. Projections and orthogonalization/4. Orthogonal and parallel vector components.srt 14KB
  215. 9. Matrix inverse/4. The MCA algorithm to compute the inverse.srt 14KB
  216. 3. Introduction to matrices/4. A zoo of matrices.srt 14KB
  217. 12. Eigendecomposition/8. Eigendecomposition by hand two examples.srt 14KB
  218. 2. Vectors/27. Basis.srt 14KB
  219. 5. Matrix rank/5. Rank of added and multiplied matrices.srt 14KB
  220. 8. Matrix determinant/6. Code challenge determinant of shifted matrices.vtt 14KB
  221. 2. Vectors/24. Span.srt 14KB
  222. 14. Quadratic form and definiteness/5. Code challenge Visualize the normalized quadratic form.srt 14KB
  223. 13. Singular value decomposition/2. Singular value decomposition (SVD).vtt 14KB
  224. 13. Singular value decomposition/3. Code challenge SVD vs. eigendecomposition for square symmetric matrices.vtt 14KB
  225. 7. Solving systems of equations/4. Gaussian elimination.vtt 13KB
  226. 5. Matrix rank/11. Making a matrix full-rank by shifting.srt 13KB
  227. 4. Matrix multiplications/10. Code challenge Pure and impure rotation matrices.srt 13KB
  228. 13. Singular value decomposition/5. Spectral theory of matrices.vtt 13KB
  229. 12. Eigendecomposition/16. Generalized eigendecomposition.srt 13KB
  230. 5. Matrix rank/2. Rank concepts, terms, and applications.srt 13KB
  231. 12. Eigendecomposition/7. Finding eigenvectors.vtt 13KB
  232. 6. Matrix spaces/7. Example of the four subspaces.srt 13KB
  233. 11. Least-squares for model-fitting in statistics/5. Least-squares via row-reduction.srt 13KB
  234. 11. Least-squares for model-fitting in statistics/7. Least-squares application 1.vtt 13KB
  235. 2. Vectors/18. Hermitian transpose (a.k.a. conjugate transpose).vtt 13KB
  236. 13. Singular value decomposition/6. SVD for low-rank approximations.srt 13KB
  237. 9. Matrix inverse/2. Matrix inverse Concept and applications.vtt 13KB
  238. 14. Quadratic form and definiteness/2. The quadratic form in algebra.vtt 13KB
  239. 2. Vectors/20. Code challenge dot products with unit vectors.srt 13KB
  240. 12. Eigendecomposition/12. Eigenvectors of repeated eigenvalues.vtt 13KB
  241. 14. Quadratic form and definiteness/3. The quadratic form in geometry.vtt 13KB
  242. 5. Matrix rank/9. Rank of A^TA and AA^T.srt 13KB
  243. 4. Matrix multiplications/9. 2D transformation matrices.vtt 13KB
  244. 4. Matrix multiplications/12. Additive and multiplicative symmetric matrices.vtt 13KB
  245. 13. Singular value decomposition/10. Code challenge Create matrix with desired condition number.vtt 13KB
  246. 11. Least-squares for model-fitting in statistics/3. Least-squares via left inverse.srt 13KB
  247. 13. Singular value decomposition/7. Convert singular values to percent variance.vtt 13KB
  248. 4. Matrix multiplications/3. Four ways to think about matrix multiplication.srt 13KB
  249. 2. Vectors/12. Code challenge dot product sign and scalar multiplication.vtt 13KB
  250. 8. Matrix determinant/5. Determinant of a 3x3 matrix.vtt 13KB
  251. 3. Introduction to matrices/4. A zoo of matrices.vtt 13KB
  252. 10. Projections and orthogonalization/4. Orthogonal and parallel vector components.vtt 12KB
  253. 2. Vectors/27. Basis.vtt 12KB
  254. 12. Eigendecomposition/9. Diagonalization.srt 12KB
  255. 9. Matrix inverse/4. The MCA algorithm to compute the inverse.vtt 12KB
  256. 14. Quadratic form and definiteness/8. Quadratic form of generalized eigendecomposition.srt 12KB
  257. 4. Matrix multiplications/16. Multiplication of two symmetric matrices.srt 12KB
  258. 10. Projections and orthogonalization/2. Projections in R^2.srt 12KB
  259. 12. Eigendecomposition/8. Eigendecomposition by hand two examples.vtt 12KB
  260. 5. Matrix rank/5. Rank of added and multiplied matrices.vtt 12KB
  261. 2. Vectors/24. Span.vtt 12KB
  262. 14. Quadratic form and definiteness/5. Code challenge Visualize the normalized quadratic form.vtt 12KB
  263. 2. Vectors/2. Algebraic and geometric interpretations of vectors.srt 12KB
  264. 5. Matrix rank/2. Rank concepts, terms, and applications.vtt 12KB
  265. 5. Matrix rank/11. Making a matrix full-rank by shifting.vtt 12KB
  266. 13. Singular value decomposition/8. SVD, matrix inverse, and pseudoinverse.srt 12KB
  267. 12. Eigendecomposition/16. Generalized eigendecomposition.vtt 12KB
  268. 4. Matrix multiplications/10. Code challenge Pure and impure rotation matrices.vtt 12KB
  269. 11. Least-squares for model-fitting in statistics/5. Least-squares via row-reduction.vtt 12KB
  270. 6. Matrix spaces/7. Example of the four subspaces.vtt 12KB
  271. 13. Singular value decomposition/6. SVD for low-rank approximations.vtt 11KB
  272. 5. Matrix rank/9. Rank of A^TA and AA^T.vtt 11KB
  273. 2. Vectors/20. Code challenge dot products with unit vectors.vtt 11KB
  274. 11. Least-squares for model-fitting in statistics/3. Least-squares via left inverse.vtt 11KB
  275. 9. Matrix inverse/6. Code challenge inverse of a diagonal matrix.srt 11KB
  276. 4. Matrix multiplications/3. Four ways to think about matrix multiplication.vtt 11KB
  277. 12. Eigendecomposition/9. Diagonalization.vtt 11KB
  278. 14. Quadratic form and definiteness/8. Quadratic form of generalized eigendecomposition.vtt 11KB
  279. 4. Matrix multiplications/16. Multiplication of two symmetric matrices.vtt 11KB
  280. 12. Eigendecomposition/11. Eigenvectors of distinct eigenvalues.srt 11KB
  281. 3. Introduction to matrices/13. Code challenge linearity of trace.srt 11KB
  282. 10. Projections and orthogonalization/2. Projections in R^2.vtt 11KB
  283. 7. Solving systems of equations/7. Code challenge RREF of matrices with different sizes and ranks.srt 11KB
  284. 4. Matrix multiplications/15. Code challenge symmetry of combined symmetric matrices.srt 11KB
  285. 2. Vectors/15. Outer product.srt 11KB
  286. 2. Vectors/2. Algebraic and geometric interpretations of vectors.vtt 11KB
  287. 13. Singular value decomposition/9. Condition number of a matrix.srt 10KB
  288. 10. Projections and orthogonalization/5. Code challenge decompose vector to orthogonal components.srt 10KB
  289. 4. Matrix multiplications/18. Frobenius dot product.srt 10KB
  290. 13. Singular value decomposition/8. SVD, matrix inverse, and pseudoinverse.vtt 10KB
  291. 4. Matrix multiplications/4. Code challenge matrix multiplication by layering.srt 10KB
  292. 4. Matrix multiplications/2. Introduction to standard matrix multiplication.srt 10KB
  293. 14. Quadratic form and definiteness/9. Matrix definiteness, geometry, and eigenvalues.srt 10KB
  294. 2. Vectors/17. Vectors with complex numbers.srt 10KB
  295. 1. Introductions/1. What is linear algebra.srt 10KB
  296. 9. Matrix inverse/9. Pseudo-inverse, part 1.srt 10KB
  297. 7. Solving systems of equations/8. Matrix spaces after row reduction.srt 10KB
  298. 5. Matrix rank/8. Code challenge reduced-rank matrix via multiplication.srt 10KB
  299. 11. Least-squares for model-fitting in statistics/4. Least-squares via orthogonal projection.srt 10KB
  300. 9. Matrix inverse/6. Code challenge inverse of a diagonal matrix.vtt 10KB
  301. 3. Introduction to matrices/2. Matrix terminology and dimensionality.srt 10KB
  302. 2. Vectors/21. Dimensions and fields in linear algebra.srt 10KB
  303. 7. Solving systems of equations/5. Echelon form and pivots.srt 10KB
  304. 12. Eigendecomposition/11. Eigenvectors of distinct eigenvalues.vtt 10KB
  305. 3. Introduction to matrices/13. Code challenge linearity of trace.vtt 9KB
  306. 13. Singular value decomposition/4. SVD and the four subspaces.srt 9KB
  307. 10. Projections and orthogonalization/9. Code challenge Inverse via QR.srt 9KB
  308. 2. Vectors/13. Code challenge is the dot product commutative.srt 9KB
  309. 2. Vectors/5. Vector-vector multiplication the dot product.srt 9KB
  310. 4. Matrix multiplications/15. Code challenge symmetry of combined symmetric matrices.vtt 9KB
  311. 2. Vectors/15. Outer product.vtt 9KB
  312. 7. Solving systems of equations/7. Code challenge RREF of matrices with different sizes and ranks.vtt 9KB
  313. 13. Singular value decomposition/9. Condition number of a matrix.vtt 9KB
  314. 4. Matrix multiplications/18. Frobenius dot product.vtt 9KB
  315. 10. Projections and orthogonalization/5. Code challenge decompose vector to orthogonal components.vtt 9KB
  316. 8. Matrix determinant/4. Determinant of a 2x2 matrix.srt 9KB
  317. 4. Matrix multiplications/2. Introduction to standard matrix multiplication.vtt 9KB
  318. 4. Matrix multiplications/4. Code challenge matrix multiplication by layering.vtt 9KB
  319. 14. Quadratic form and definiteness/9. Matrix definiteness, geometry, and eigenvalues.vtt 9KB
  320. 5. Matrix rank/12. Code challenge is this vector in the span of this set.srt 9KB
  321. 2. Vectors/17. Vectors with complex numbers.vtt 9KB
  322. 1. Introductions/1. What is linear algebra.vtt 9KB
  323. 8. Matrix determinant/2. Determinant concept and applications.srt 9KB
  324. 2. Vectors/6. Code challenge dot products with matrix columns.srt 9KB
  325. 9. Matrix inverse/9. Pseudo-inverse, part 1.vtt 9KB
  326. 6. Matrix spaces/8. More on Ax=b and Ax=0.srt 9KB
  327. 3. Introduction to matrices/2. Matrix terminology and dimensionality.vtt 9KB
  328. 11. Least-squares for model-fitting in statistics/4. Least-squares via orthogonal projection.vtt 9KB
  329. 7. Solving systems of equations/8. Matrix spaces after row reduction.vtt 9KB
  330. 5. Matrix rank/8. Code challenge reduced-rank matrix via multiplication.vtt 9KB
  331. 2. Vectors/21. Dimensions and fields in linear algebra.vtt 9KB
  332. 7. Solving systems of equations/5. Echelon form and pivots.vtt 8KB
  333. 5. Matrix rank/10. Code challenge rank of multiplied and summed matrices.srt 8KB
  334. 6. Matrix spaces/5. Columnleft-null and rownull spaces are orthogonal.srt 8KB
  335. 3. Introduction to matrices/9. Transpose.srt 8KB
  336. 11. Least-squares for model-fitting in statistics/6. Model-predicted values and residuals.srt 8KB
  337. 2. Vectors/4. Vector-scalar multiplication.srt 8KB
  338. 2. Vectors/16. Vector cross product.srt 8KB
  339. 13. Singular value decomposition/4. SVD and the four subspaces.vtt 8KB
  340. 2. Vectors/5. Vector-vector multiplication the dot product.vtt 8KB
  341. 12. Eigendecomposition/6. Code challenge eigenvalues of random matrices.srt 8KB
  342. 10. Projections and orthogonalization/9. Code challenge Inverse via QR.vtt 8KB
  343. 2. Vectors/13. Code challenge is the dot product commutative.vtt 8KB
  344. 4. Matrix multiplications/6. Order-of-operations on matrices.srt 8KB
  345. 8. Matrix determinant/4. Determinant of a 2x2 matrix.vtt 8KB
  346. 14. Quadratic form and definiteness/4. The normalized quadratic form.srt 8KB
  347. 14. Quadratic form and definiteness/10. Proof A^TA is always positive (semi)definite.srt 8KB
  348. 8. Matrix determinant/3. Code challenge determinant of small and large singular matrices.srt 8KB
  349. 8. Matrix determinant/2. Determinant concept and applications.vtt 8KB
  350. 5. Matrix rank/12. Code challenge is this vector in the span of this set.vtt 8KB
  351. 2. Vectors/6. Code challenge dot products with matrix columns.vtt 8KB
  352. 6. Matrix spaces/8. More on Ax=b and Ax=0.vtt 8KB
  353. 2. Vectors/3. Vector addition and subtraction.srt 7KB
  354. 1. Introductions/2. Linear algebra applications.srt 7KB
  355. 3. Introduction to matrices/6. Matrix addition and subtraction.srt 7KB
  356. 2. Vectors/4. Vector-scalar multiplication.vtt 7KB
  357. 5. Matrix rank/10. Code challenge rank of multiplied and summed matrices.vtt 7KB
  358. 6. Matrix spaces/6. Dimensions of columnrownull spaces.srt 7KB
  359. 6. Matrix spaces/5. Columnleft-null and rownull spaces are orthogonal.vtt 7KB
  360. 3. Introduction to matrices/9. Transpose.vtt 7KB
  361. 11. Least-squares for model-fitting in statistics/6. Model-predicted values and residuals.vtt 7KB
  362. 2. Vectors/16. Vector cross product.vtt 7KB
  363. 9. Matrix inverse/3. Inverse of a 2x2 matrix.srt 7KB
  364. 2. Vectors/7. Vector length.srt 7KB
  365. 14. Quadratic form and definiteness/6. Eigenvectors and the quadratic form surface.srt 7KB
  366. 3. Introduction to matrices/12. Diagonal and trace.srt 7KB
  367. 12. Eigendecomposition/6. Code challenge eigenvalues of random matrices.vtt 7KB
  368. 7. Solving systems of equations/3. Converting systems of equations to matrix equations.srt 7KB
  369. 4. Matrix multiplications/6. Order-of-operations on matrices.vtt 7KB
  370. 12. Eigendecomposition/5. Code challenge eigenvalues of diagonal and triangular matrices.srt 7KB
  371. 14. Quadratic form and definiteness/4. The normalized quadratic form.vtt 7KB
  372. 14. Quadratic form and definiteness/10. Proof A^TA is always positive (semi)definite.vtt 7KB
  373. 12. Eigendecomposition/15. Code challenge trace and determinant, eigenvalues sum and product.srt 7KB
  374. 3. Introduction to matrices/8. Code challenge is matrix-scalar multiplication a linear operation.srt 7KB
  375. 8. Matrix determinant/3. Code challenge determinant of small and large singular matrices.vtt 7KB
  376. 2. Vectors/19. Interpreting and creating unit vectors.srt 7KB
  377. 2. Vectors/23. Subspaces vs. subsets.srt 7KB
  378. 6. Matrix spaces/6. Dimensions of columnrownull spaces.vtt 7KB
  379. 2. Vectors/3. Vector addition and subtraction.vtt 7KB
  380. 1. Introductions/2. Linear algebra applications.vtt 7KB
  381. 3. Introduction to matrices/6. Matrix addition and subtraction.vtt 7KB
  382. 8. Matrix determinant/7. Find matrix values for a given determinant.srt 6KB
  383. 4. Matrix multiplications/17. Code challenge standard and Hadamard multiplication for diagonal matrices.srt 6KB
  384. 14. Quadratic form and definiteness/6. Eigenvectors and the quadratic form surface.vtt 6KB
  385. 3. Introduction to matrices/12. Diagonal and trace.vtt 6KB
  386. 9. Matrix inverse/3. Inverse of a 2x2 matrix.vtt 6KB
  387. 2. Vectors/7. Vector length.vtt 6KB
  388. 4. Matrix multiplications/11. Additive and multiplicative matrix identities.srt 6KB
  389. 7. Solving systems of equations/3. Converting systems of equations to matrix equations.vtt 6KB
  390. 12. Eigendecomposition/5. Code challenge eigenvalues of diagonal and triangular matrices.vtt 6KB
  391. 12. Eigendecomposition/15. Code challenge trace and determinant, eigenvalues sum and product.vtt 6KB
  392. 3. Introduction to matrices/8. Code challenge is matrix-scalar multiplication a linear operation.vtt 6KB
  393. 2. Vectors/19. Interpreting and creating unit vectors.vtt 6KB
  394. 2. Vectors/23. Subspaces vs. subsets.vtt 6KB
  395. 1. Introductions/3. How best to learn from this course.srt 6KB
  396. 8. Matrix determinant/7. Find matrix values for a given determinant.vtt 6KB
  397. 6. Matrix spaces/3. Row space of a matrix.srt 6KB
  398. 4. Matrix multiplications/11. Additive and multiplicative matrix identities.vtt 6KB
  399. 4. Matrix multiplications/17. Code challenge standard and Hadamard multiplication for diagonal matrices.vtt 6KB
  400. 4. Matrix multiplications/19. What about matrix division.srt 5KB
  401. 12. Eigendecomposition/14. Eigendecomposition of singular matrices.srt 5KB
  402. 1. Introductions/3. How best to learn from this course.vtt 5KB
  403. 1. Introductions/4. Using MATLAB, Octave, or Python in this course.srt 5KB
  404. 6. Matrix spaces/3. Row space of a matrix.vtt 5KB
  405. 4. Matrix multiplications/5. Matrix multiplication with a diagonal matrix.srt 5KB
  406. 4. Matrix multiplications/19. What about matrix division.vtt 5KB
  407. 12. Eigendecomposition/14. Eigendecomposition of singular matrices.vtt 5KB
  408. 1. Introductions/4. Using MATLAB, Octave, or Python in this course.vtt 4KB
  409. 4. Matrix multiplications/5. Matrix multiplication with a diagonal matrix.vtt 4KB
  410. 9. Matrix inverse/10. Code challenge pseudoinverse of invertible matrices.srt 4KB
  411. 9. Matrix inverse/8. Proof the inverse is unique.srt 4KB
  412. 9. Matrix inverse/10. Code challenge pseudoinverse of invertible matrices.vtt 3KB
  413. 4. Matrix multiplications/13. Hadamard (element-wise) multiplication.srt 3KB
  414. 9. Matrix inverse/8. Proof the inverse is unique.vtt 3KB
  415. 2. Vectors/14. Vector Hadamard multiplication.srt 3KB
  416. 1. Introductions/5. Leaving reviews, course coupons.srt 3KB
  417. 4. Matrix multiplications/13. Hadamard (element-wise) multiplication.vtt 3KB
  418. 10. Projections and orthogonalization/8. Matrix inverse via QR decomposition.srt 3KB
  419. 1. Introductions/5. Leaving reviews, course coupons.vtt 3KB
  420. 2. Vectors/14. Vector Hadamard multiplication.vtt 3KB
  421. 10. Projections and orthogonalization/8. Matrix inverse via QR decomposition.vtt 2KB
  422. 12. Eigendecomposition/4. Shortcut for eigenvalues of a 2x2 matrix.srt 2KB
  423. 3. Introduction to matrices/10. Complex matrices.srt 2KB
  424. 15. Discount coupons for related courses/1. Bonus Links to related courses.html 2KB
  425. 12. Eigendecomposition/4. Shortcut for eigenvalues of a 2x2 matrix.vtt 2KB
  426. 3. Introduction to matrices/10. Complex matrices.vtt 2KB
  427. 3. Introduction to matrices/7. Matrix-scalar multiplication.srt 2KB
  428. 3. Introduction to matrices/7. Matrix-scalar multiplication.vtt 2KB
  429. 2. Vectors/10. Vector orthogonality.html 144B
  430. 2. Vectors/11. Relative vector angles.html 144B
  431. 2. Vectors/25. In the span.html 144B
  432. 2. Vectors/8. Vector length in MATLAB.html 144B
  433. 3. Introduction to matrices/11. Addition, equality, and transpose.html 144B
  434. 3. Introduction to matrices/3. Matrix sizes and dimensionality.html 144B
  435. 3. Introduction to matrices/5. Can the matrices be concatenated.html 144B
  436. 4. Matrix multiplications/14. Matrix operation equality.html 144B
  437. 4. Matrix multiplications/8. Find the missing value!.html 144B
  438. 5. Matrix rank/3. Maximum possible rank..html 144B
  439. 5. Matrix rank/6. What's the maximum possible rank.html 144B
  440. 4. Matrix multiplications/1. Exercises + code.html 87B
  441. 11. Least-squares for model-fitting in statistics/1. Exercises + code.html 86B
  442. 5. Matrix rank/1. Exercises + code.html 85B
  443. 9. Matrix inverse/1. Exercises + code.html 85B
  444. 2. Vectors/1. Exercises + code.html 80B
  445. 10. Projections and orthogonalization/1. Exercises + code.html 76B
  446. 3. Introduction to matrices/1. Exercises + code.html 75B
  447. 14. Quadratic form and definiteness/1. Exercises + code.html 55B
  448. 8. Matrix determinant/1. Exercises.html 52B
  449. [DesireCourse.Com].url 51B
  450. 7. Solving systems of equations/1. Exercises + code.html 40B
  451. 6. Matrix spaces/1. Exercises + code.html 36B
  452. 12. Eigendecomposition/1. Exercises + code.html 33B
  453. 13. Singular value decomposition/1. Exercises + code.html 26B