Linear algbera #3: projections, orthogonalization, and leastsquares
Mike X Cohen, Neuroscientist, teacher, writer


Projections in R^2
9:37 
Projections in R^N
14:08 
Orthogonal and parallel vector components
10:55 
Code challenge: decompose vector to orthogonal components
8:57 
Orthogonal matrices
13:44 
GramSchmidt and QR decomposition
15:39 
Matrix inverse via QR decomposition
2:26 
Code challenge: Inverse via QR
7:52 
Introduction to leastsquares
12:55 
Leastsquares via left inverse
10:49 
Leastsquares via orthogonal projection
7:55 
Leastsquares via rowreduction
10:50 
Modelpredicted values and residuals
6:32 
Leastsquares application 1
12:22 
Leastsquares application 2
18:14

About This Class
This class follows from linear algebra #12.
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Officially I'm Dr. Michael X Cohen, but I prefer just "Mike" or "Mike X" or "the mysterious X." I'm a scientist because I believe that discovery and the drive to understand mysteries are among the most important drivers of progress in human civilization. And I believe in teaching because, well, because I really like teaching. I've been doing it my whole life. I teach "reallife" courses, online courses, university courses. I've written several books about neuroscience and data analysis, which...