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Linear Algebra (Youtube)
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Matrices, vectors, vector spaces, transformations. Covers all topics in a first year college linear algebra course. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra. less
43 vídeos se encuentrans.


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Distance between planes | Vectors and spaces | Linear Algebra | Khan Academy14:450
Point distance to plane | Vectors and spaces | Linear Algebra | Khan Academy12:120
Normal vector from plane equation | Vectors and spaces | Linear Algebra | Khan Academy9:580
Vector triple product expansion (very optional) | Vectors and spaces | Linear Algebra | Khan Academy14:250
Showing that an eigenbasis makes for good coordinate systems | Linear Algebra | Khan Academy13:900
Eigenvectors and eigenspaces for a 3x3 matrix | Linear Algebra | Khan Academy15:340
Eigenvalues of a 3x3 matrix | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy14:800
Finding eigenvectors and eigenspaces example | Linear Algebra | Khan Academy14:340
Example solving for the eigenvalues of a 2x2 matrix | Linear Algebra | Khan Academy5:390
Proof of formula for determining eigenvalues | Linear Algebra | Khan Academy9:190
Introduction to eigenvalues and eigenvectors | Linear Algebra | Khan Academy7:430
Gram-Schmidt example with 3 basis vectors | Linear Algebra | Khan Academy13:570
Gram-Schmidt process example | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy13:140
The Gram-Schmidt process | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy19:240
Orthogonal matrices preserve angles and lengths | Linear Algebra | Khan Academy11:160
Example using orthogonal change-of-basis matrix to find transformation matrix | Khan Academy27:400
Finding projection onto subspace with orthonormal basis example | Linear Algebra | Khan Academy6:420
Projections onto subspaces with orthonormal bases | Linear Algebra | Khan Academy16:140
Coordinates with respect to orthonormal bases | Linear Algebra | Khan Academy15:280
Introduction to orthonormal bases | Linear Algebra | Khan Academy11:160
Changing coordinate systems to help find a transformation matrix | Linear Algebra | Khan Academy29:000
Alternate basis transformation matrix example part 2 | Linear Algebra | Khan Academy12:360
Alternate basis transformation matrix example | Linear Algebra | Khan Academy13:200
Transformation matrix with respect to a basis | Linear Algebra | Khan Academy18:200
Invertible change of basis matrix | Linear Algebra | Khan Academy13:340
Change of basis matrix | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy17:550
Coordinates with respect to a basis | Linear Algebra | Khan Academy16:800
Least squares examples | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy18:500
Another least squares example | Alternate coordinate systems (bases) | Linear Algebra | Khan Academy13:250
Least squares approximation | Linear Algebra | Khan Academy15:320
Projection is closest vector in subspace | Linear Algebra | Khan Academy9:500
Another example of a projection matrix | Linear Algebra | Khan Academy21:360
Subspace projection matrix example | Linear Algebra | Khan Academy13:400
A projection onto a subspace is a linear transformation | Linear Algebra | Khan Academy16:160
Visualizing a projection onto a plane | Linear Algebra | Khan Academy9:280
Projections onto subspaces | Linear Algebra | Khan Academy17:260
Showing that A-transpose x A is invertible | Matrix transformations | Linear Algebra | Khan Academy12:340
Rowspace solution to Ax = b example | Linear Algebra | Khan Academy19:380
Unique rowspace solution to Ax = b | Linear Algebra | Khan Academy19:120
Orthogonal complement of the nullspace | Linear Algebra | Khan Academy3:270
Orthogonal complement of the orthogonal complement | Linear Algebra | Khan Academy12:180
Representing vectors in rn using subspace members | Linear Algebra | Khan Academy27:100
dim(v) + dim(orthogonal complement of v) = n | Linear Algebra | Khan Academy9:270


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