Types of problems you can apply the fastai library to

Application fields

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.


This submodule handles the collaborative filtering problems.


This sub-package deals with tabular (or structured) data.


This sub-package contains everything you need for Natural Language Processing.


This sub-package contains the classes that deal with Computer Vision.

Module structure

In each case (except for collab), the module is organized this way:


This sub-module deals with the pre-processing (data augmentation for images, cleaning for tabular data, tokenizing and numericalizing for text).


This sub-module defines the dataset class(es) to deal with this kind of data.


This sub-module defines the specific models used for this kind of data.


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

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