More often than not, people who ask what is Machine Learning and how to get into it get stricken by a template answer: GO LEARN ZILLION FIELDS IN MATHEMATICS FIRST without event getting the chance to understand machine learning beyond “Oh boy, it’s a machine that is learning to make predictions”.
disclaimer: mathematics is important but it’s not the first thing.
Surely mathematics is important, but if someone told me when I was 12 years old trying to learn C++ that I should quit and go learn linear algebra in order to become a programmer, probably I wouldn’t have even got the chance to know if programming is something I can learn professionally later in life.
This approach works very well up until a certain type of problems comes into play.
Look, programming is cool but in order to write a program that solves the problems we humans can solve but cannot describe exactly how we solve it, programming fails.
Experienced dermatologists can detect skin cancer, but they cannot describe exactly how they detect it, it’s just beyond their brain capabilities. it takes years of a practitioner to learn how to do it more accurately.
A car driver can seamlessly drive in a crowd or on a highway, but when you try to learn from them, all they say is that you should not care about surrounding people and only focus on your lane and other nonsense that you cannot describe to a computer.