The proc_df function from fastai.structured is not available in fastai V1; you are supposed to pass ‘Categorify’ etc. as procs to the data block API. This works great for the standard models (like with the tabular learner).
But how do you use the fastai preprocessing pipeline for models that do not use databunches (like a random forest from sklearn)? Or what do you do if you want to compare a deep learning model to a classical model on the same data?
@muellerzr, How would I use this for new data? let’s say the model is deployed and I want to process new data. with sklearn I could create a pipeline and make sure any new data will go through the sklearn pipeline to make sure it uses a transformer object that was fitted to the training set. is there a way to do the same with fastai procs(i.e Categorify, FillMissing and Normalize)?