Software component developers tend to be far removed from the end users of the products in which their components are employed. Recently, however, we connected directly with a KOMPAS-3D MCAD user to solve an issue involving mold design. It seems that 3D models were being exported incorrectly to data exchange formats like STP, X_T, and SAT. The cause, unhappily for us, turned out to be in our С3D Modeler geometric modeling kernel. Here is how we solved the problem, quickly.
When you study an abstract subject like linear algebra, you may wonder: why do you need all these vectors and matrices? How are you going to apply all this inversions, transpositions, eigenvector and eigenvalues for practical purposes?
Well, if you study linear algebra with the purpose of doing machine learning, this is the answer for you.
In brief, you can use linear algebra for machine learning on 3 different levels:
application of a model to data;
training the model;
understanding how it works or why it does not work.
