Poor analogy, I think. "Using ML" in the same way most of us "use" CPUs is ~ equivalent to using Google Translate or OCR through an API at best.
For a software engineer building systems with requirements expressed as concrete specs, based on established and well-documented methods and tools, knowing nothing else but coding might be enough. Even in such cases, understanding the details can be highly beneficial (given the state of the field). However, IMO, wanting to be a "data scientist", "analyst" or similar without knowing any of the science at the foundation of the field just because "you can read it when you need it" is more like wanting to fly an airplane with little to no training just because autopilots are decent and there are plenty of manuals if really needed.
Spaniard, manager by day, dev by night. node.js express alexa jquery html5 css but can also do java php, and if you really insist I'll dust off my C LISP Prolog ML Miranda and even assembly.
I honestly believe some math is needed to work in the field. You should at least understand the concepts, which is doable with just one Calculus semester at graduate level. Nowadays, with MOOCs, Khan Academy, etc. this is definitely doable by anyone with a logical, structured mind. It just takes time and some effort. Precisely what it takes to learn any new trade.
This doesn't mean that if you know the math, you automatically qualify as a ML professional. But it will help you to "get it", as the most difficult bits you already master.
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Poor analogy, I think. "Using ML" in the same way most of us "use" CPUs is ~ equivalent to using Google Translate or OCR through an API at best.
For a software engineer building systems with requirements expressed as concrete specs, based on established and well-documented methods and tools, knowing nothing else but coding might be enough. Even in such cases, understanding the details can be highly beneficial (given the state of the field). However, IMO, wanting to be a "data scientist", "analyst" or similar without knowing any of the science at the foundation of the field just because "you can read it when you need it" is more like wanting to fly an airplane with little to no training just because autopilots are decent and there are plenty of manuals if really needed.
Your example is spot on!
I honestly believe some math is needed to work in the field. You should at least understand the concepts, which is doable with just one Calculus semester at graduate level. Nowadays, with MOOCs, Khan Academy, etc. this is definitely doable by anyone with a logical, structured mind. It just takes time and some effort. Precisely what it takes to learn any new trade.
This doesn't mean that if you know the math, you automatically qualify as a ML professional. But it will help you to "get it", as the most difficult bits you already master.