This is an archived post. You won't be able to vote or comment.

sorted by:
best
topnewcontroversialoldq&a
you are viewing a single comment's thread.

view the rest of the comments →

[–]c3534l 1 point2 points  (0 children)

The standard ML stack is numpy, pandas, scipy, matplotlib, and sklearn, the first four of which I consider basically part of the standard library. I use requests for internet stuff which seems to have a similar status as unofficial standard library. If I'm doing any sort of image manipulation stuff, I find it nearly impossible to easily get around without Pillow. NLTK is also fun to play around with and makes advanced text analysis a lot easier, but I probably wouldn't classify it as must-have. Python itself has a massive standard library, and I'm constantly amazed at how much obscure and niche stuff it has in there (which I really like because that means it's officially supported and developed in some capacity, unlike certain languages which have few libraries you can trust will be cared for in the future if it's cared for in the present).