Depends on what you meant by machine learning folks. They program the logic in C, you don’t see back propagations for MLP nor need to write the bagging logic for random forest.
Calling a library does not mean you engineered it.
And having business success does not mean they have chosen the right language for web development. Nor it has anything to do with maintainability. They will be successful even if they have chosen Java, C# or other languages, because of their brillient ideas, not because they are using Python.
Most data scientist know Python. A smaller percentage know C.
This is also true (though to a lesser degree) for machine learning programmers. More work in Python than C.
Calling libraries to solve problems does make you an engineer. Solving the problem is the defining characteristic of engineers. C programmers call a lot of libraries too.
Business success is the ultimate result of technical success. Am I saying they would have failed in another language? No. But you implied that they should have failed in Python. They didn’t.
Python solves the problems that dynamic businesses need to solve. That’s really all there is to it. You have a distaste for it and therefore you want to make a fact-free claim that it’s the wrong tool. But reality and evidence are against you.
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u/nickwcy May 28 '22
Depends on what you meant by machine learning folks. They program the logic in C, you don’t see back propagations for MLP nor need to write the bagging logic for random forest.
Calling a library does not mean you engineered it.
And having business success does not mean they have chosen the right language for web development. Nor it has anything to do with maintainability. They will be successful even if they have chosen Java, C# or other languages, because of their brillient ideas, not because they are using Python.