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by ivansavz
4492 days ago
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{arithmetic}
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{vecops} = {Vector operations}
{dotproduct}
{arithmetic}
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{RREF} = {Reduced row echelon form}
{arithmetic}
| {patience}
| | {dotproduct}
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{matrices}
{Mops} = {Matrix operations}
{Meqns} = {Matrix equations}
{Mmult} = {Matrix multiplication}
{Mdet} = {Determinants}
{Minv} = {Matrix inverse}
{y=mx+b}
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{linear} = {Linearity}
{plane} = {Lines and planes}
{dotproduct}
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{proj} = {Projections}
{basis} = {Coordinate projections}
{vectors}
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{VS1} = {Vector spaces}
{VS2} = {Abstract vector spaces} // knowledge buzz moment
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| {dotproduct}
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{IPS} = {Abstract inner product spaces}
{y=mx}
| {Mmult}
| | {function f:R->R}
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{linT} = {Linear transformations}
{VSRREF} = {Vector space techniques for matrices}
{TasM} = {Finding matrix representations}
{basis2} = {Change of basis for matrices}
{Mmult}
| {linT}
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{eigV} = {Eigenvalues and eigenvectors}
{Mdecomp}= {Matrix decompositions}
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{specM} = {Special types of matrices}
{VS1}
|{plane}
||{eigV}
|||{linT}
|||||{Meqns}
||||||{Mmult}
||||||||{Mdet}
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{invMthm} = {Invertible matrix theorem}
{proj}
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{GSorth} = {Gram--Schmidt orthogonalization}
{RREF}
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{LP} = {Linear programming}
{Mmult}
|{Meqn}
||{RREF}
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{solve} = {Solving systems of equations}
{LSaprx} = {Least squares approximate solution}
{ML} = {Machine learning}
{LAoverZ_q}= {Linear algebra over a finite field}
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||{ECCs} = {Error correcting codes}
|{crypto} = {Cryptography}
{netcode}= {Network coding}
{trig}
|{taylor}
||{AVS}
|||{IPS}
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{fourier}= {Fourier series}
{fourier}
| {prob} = {Probability density}
| | {LAoverC}= {Linear algebra with complex numbers}
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{quantum}= {Quantum mechanics}
UPDATE: Okay so if anyone is interested, I just put up a pre-release of the book https://gum.co/noBSLA |
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