from fastai.gen_doc.nbdoc import *
from fastai.tabular import *
show_doc(tabular_learner)
tabular_learner[source][test]
tabular_learner(data:DataBunch,layers:Collection[int],emb_szs:Dict[str,int]=*None,metrics=None,ps:Collection[float]=None,emb_drop:float=0.0,y_range:OptRange=None,use_bn:bool=True, ***learn_kwargs**)
No tests found for tabular_learner. To contribute a test please refer to this guide and this discussion.
Get a Learner using data, with metrics, including a TabularModel created using the remaining params.
You can customize the automatic embeddings sizes picked by the library by passing a dictionary emb_szs to match categorical variable names with an embedding size. emb_drop, ps. y_range and use_bn are passed to TabularModel, the kwargs are passed to Learner. See tabular for an example of use.