Neural Networks from Scratch in Python by Harrison Kinsley, Daniel Kukie a

Chapter 2 - Coding Our First Neurons - Neural Networks from Scratch in Python
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Transposition for the Matrix Product
How did we suddenly go from 2 vectors to row and column vectors? We used the relation of the
dot product and matrix product saying that a dot product of two vectors equals a matrix product of
a row and column vector (the arrows above the letters signify that they are vectors):
We also have temporarily used some simplification, not showing that column vector ​b​ is actually
a ​transposed​ vector ​b​.​ ​The proper equation, matching the dot product of vectors ​a​ and ​b​ written
as matrix product should look like:
Here we introduced one more new operation ​—​ ​transposition​. Transposition simply modifies a
matrix in a way that its rows become columns and columns become rows:
Fig 2.16:​ Example of an array transposition.
Anim 2.16:​ ​https://nnfs.io/qut