There is a lot of published research work in ML that had huge impact without explicitly touching linear algebra.
Given that is the case, to answer your question: yes, linear algebra is the foundation of ML. No, a lot of impactful day-to-day ML engineering can be done without touching linear algebra.
This is how assembly is the basis of compilation and programming. But you probably are going to get a whole lot of work done without ever using it.
It's generally a nice flex when applicants can code assembly, and usually a yellow-flag when the company suggests they require knowledge of assembly.
To me, my eyebrows raise when an industry person mentions linear algebra. I'm just saying the odds are really low that you actually use it.
Given that is the case, to answer your question: yes, linear algebra is the foundation of ML. No, a lot of impactful day-to-day ML engineering can be done without touching linear algebra.
This is how assembly is the basis of compilation and programming. But you probably are going to get a whole lot of work done without ever using it.
It's generally a nice flex when applicants can code assembly, and usually a yellow-flag when the company suggests they require knowledge of assembly.
To me, my eyebrows raise when an industry person mentions linear algebra. I'm just saying the odds are really low that you actually use it.