lecture matrix

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1. 1▶Lec14 - Projections onto a Subspace, Least Squares and Gram-SchmidtAdvanced Engineering MathematicsNotes
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2. 2▶Lec16 - Formulas for the DeterminantsAdvanced Engineering MathematicsNotes
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3. 3▶Lecture 13: Projections and Least Squares (Continued)Advanced Engineering MathematicsNotes
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4. 4▶Lecture 12: Projections Onto a SubspaceAdvanced Engineering MathematicsNotes
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5. 5▶Lecture 9 - Independence, Basis and DimensionAdvanced Engineering MathematicsNotes
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6. 6▶Lecture 10: Dimensions of the Four Fundamental SubspacesAdvanced Engineering MathematicsNotes
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7. 7▶Lecture 8: The Complete Solution of Ax=bAdvanced Engineering MathematicsNotes
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8. 8▶Lecture 6: Reduced Row Echelon FormAdvanced Engineering MathematicsNotes
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9. 9▶Lecture 7 - Vector Spaces and Subspaces, the Column Space and the NullspaceAdvanced Engineering MathematicsNotes
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10. 10▶Lecture 5 Matrix Elimination A=LU FactorizationAdvanced Engineering MathematicsNotes
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11. 11▶Lecture 7: Subgradient method continued10-725 OptimizationNotes
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12. 12▶Lecture 6: Subgradient method10-725 OptimizationNotes
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13. 13▶Lecture 5: Gradient descent revisited10-725 OptimizationNotes
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14. 14▶Lecture 9: Acceleration10-725 OptimizationNotes
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15. 15▶Lecture 10: Matrix differentials10-725 OptimizationNotes
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16. 16▶Lecture 4: More convexity; first-order methods10-725 OptimizationNotes
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17. 17▶Lecture 3: Convexity10-725 OptimizationNotes
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18. 18▶Lecture 2: Intro; Gradient descent10-725 OptimizationNotes
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19. 19▶Lecture 1: Introduction10-725 OptimizationNotes
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20. 20▶Lecture 11: Matrix differentials; Newton's method10-725 OptimizationNotes
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