Python NumPy (Tutorial 01) - Intro to Linear Algebra

 

prototypeprj.com = zaneacademy.com (version 2.0)

00:21 add 2 matrices

(both must have same size. add elements in same position)

01:04 subtract 2 matrices

(both must have same size. subtract elements in same position)

01:30 multiply 2 matrices

(both must have matching inner dimension.

size of resulting matrix obtained by dropping middle dimension)

02:19 step by step example of multiplying 2 matrices

04:10 scalar add (operation applied to each element in matrix)

04:44 scalar subtract (operation applied to each element in matrix)

05:04 scalar multiply (operation applied to each element in matrix)

05:22 scalar divide (operation applied to each element in matrix)

05:42 identity matrix contains all 0s except diagonal is 1s

(multiply matrix by identity matrix and obtain original matrix)

06:45 transpose matrix by flipping it along diagonal.

rows become columns and columns become rows

07:20 dot product happens between 2 vectors

(here we do element-wise multiplication than sum up results)

08:54 NumPy setup using miniconda

09:22 code the application

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'Python NumPy (Tutorial 01) - Intro to Linear Algebra'

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