I just started the ML for practitioners and found out an issue there is no more existence of some useful functions for pre-processing in the latest version of fastai. So, i tried to create a pip package to solve this issue
Moreover, I have published the first pip package
Usage: !pip install fastai_ml from fastai_ml.basics import *
NOTE
Right now i have added only functions that had been used in first lecture
but i think now they are for DataBunch (not for panda’s DataFrame) and for apply these you have to separate cat and cont names etc.
Please correct me if I am wrong
You do and don’t. If you check the docs we can get the cat and cont names quickly by get_cat_cont (or something similar) and we can also function call them normally. (Though in practice you may want to decide these yourself as sometimes you may want a numerical to be categorical if it’s a one-hot representation, etc)
Thanks for your guidance … As i just started with the ML course so I’m getting trouble in applying these methods. Now I’ll check for sure. Thank you for your support
The new upcoming version of the course will be a mix, which should help some. Lesson 4 on the new lecture (Practical Deep Learning for Coders) goes into tabular too I’d recommend Intro ML for the concepts and then PDLC for a newer application of those approaches/concepts