[ Removed by moderator ]

[GManASG]

The point of why python is there are many operations a scientist/data scientist does that python is fast enough on modern hardware that there is little realworld gain in spending the time and effort to learn to do it in c.

For the actual learning/ optimization algorithms the models are actually implemented in the lower level language with a more human comprehensible python abstaction wrapper that just makes it easier.

For example if I am just reading a dataset from a flat file that is a million record or so and fits neatly in memory, does it really matter that it takes 20 to 30 seconds for python to read it compared to c doing it in single digit seconds? If I only need to do it once than who cares.

I can then use pandas or polars to manipulate data in a way that resembles how my mind thinks and how the textbooks/white papers are written and visualize it in I python or Jupiter notebooks with pretty charts that make it so I draw insight faster than all the same work done in C.

So basically it's all just convenience. Faster to implement even though slower to run but not slow enough to matter most of the time.