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You may want to take a course in Linear Algebra before getting into ML. It won't make a lot of sense unless you have a basic understanding of matrices.
A good starting point would be https://www.coursera.org/learn/datasciencemathskills also this one doesn't cover matrices as far as I remember. Andrew NG's Machine Learning course (https://www.coursera.org/learn/machine-learning/home/week/1) also has a linear algebra section in week 1 to refresh your knowledge.
There are really some great books I love Mathematics - From the Birth of Numbers which is brilliant in that you get great scope & history. Also I highly value Schaum's outlines series : Linear Algebra (Fully solved problems) walks you thru certain problems and how to solve, then gives you problems to solve, you give it a spin and the answers are provided so you can verify accordingly. I think we also have to give a shout out to the for Dummies series which are are written be great people with great imaginations to convey a thought process in a fun manner.
Get the the library and have some fun !
Greetings Frederick,
What the product operation line is saying (equation 2.5) is the cell C_{i,j} is defined as the dot product of A's row i and B's column j.
A How To video is Intro to matrix multiplication (video) | Khan Academy. This is just the tip of the iceberg for linear algebra. As other commentators noted, a refreshing class on linear algebra might be helpful.
For a mathematical reason why the definition of matrix multiplication is the way it is, see https://math.stackexchange.com/questions/271927/why-historically-do...
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