from fastai.gen_doc.nbdoc import *
The fastai library allows you to train a Model on a certain DataBunch very easily by binding them together inside a Learner object. This module regroups the tools the library provides to help you preprocess and group your data in this format.
collab¶This submodule handles the collaborative filtering problems.
tabular¶This sub-package deals with tabular (or structured) data.
text¶This sub-package contains everything you need for Natural Language Processing.
vision¶This sub-package contains the classes that deal with Computer Vision.
In each case (except for collab), the module is organized this way:
transform¶This sub-module deals with the pre-processing (data augmentation for images, cleaning for tabular data, tokenizing and numericalizing for text).
data¶This sub-module defines the dataset class(es) to deal with this kind of data.
models¶This sub-module defines the specific models used for this kind of data.
learner¶When it exists, this sub-module contains functions that will directly bind this data with a suitable model and add the necessary callbacks.
To start using any of the above applications, simply import the top level module.
All the submodules get included.
The general structure is:
from fastai.[APPLICATION] import *
For example, to use collab:
from fastai.collab import *
For more information on imports