I think the exact opposite, ML is good for automating away the trivial, repetitive tasks that take time away from development but they have a harder time with making a coherent, maintainable architecture of interconnected modules.
It is also good for data analysis, for example when the dynamics of a system are complex but you have a lot of data. In that context, the algorithm doesn’t have to infer a model that matches reality completely, just one that is close enough for the region of interest.
Gets me soooo hard
I think I know what you meant but be aware that this can be very misinterpreted.
And you can use it on GNU Not Unix!
The Nokia XR21 also has a 3.5mm jack. It’s likely weaker performance-wise but it has a battery life of approximately 3 days so it won’t run out of juice as quickly.
How is that about data security/integrity?
I thought right-hand rule with Z up as thumb was standard in science? You usually project on the xy-plane, for example when calculating the distance to objects on a flat surface.
C++ is unironically my favorite language, especially coding in python feels so ambiguous and you need to take care of so many special cases that just wouldn’t even exist in C++.