Passing in empty list works !!
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Typo in 02_permutationā¦ nb.
to = TabularPandas(ā¦should be y_block=RegressionBlock()ā¦) and not block_y =
They updated the syntax around a few days ago. Iāll go make that adjustment.
Edit: this has been fixed @Srinivas
Thanks
Thanks for the reply. I did not see them in the arguments in the doc thus thought they are deprecated. My bad!
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Hi @zdw2126062 I encountered the same error.
Does that mean having momentum does not have a positive effect on a tabular models?
Also, since momentum is not used will it be a good idea to use weight decay as an optimisation instead of momentum?
@AjayStark no see Sylvain comments about tabular_config. Iāll try to show an example next week.
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Oh, thanks for pointing out. Got it ! 
After assigning momentum using config=tabular_config(), how to pass config into tabular_learner() ?
Just pass it in as config. IE:
tabular_learner(dls, layers, config=config)
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Ooops silly one. Didnāt see config in the arguments list.
And is it same as creating a Tabularmodel first with the ps and embed_p
You can pass it in as below:-
config = tabular_config(ps=[0.001,0.01], embed_p = 0.04)
learn = tabular_learner(dls,
layers=[100,50],
config = config,
metrics=[accuracy])
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Yeah got it, Thank you
@muellerzr when is the lesson4 going to be?
Just came to know about this, how are you currently doing Zach?. Hope all itās well and do take adequate rest as required.
As mentioned earlier they are now on Wednesdays. Iām doing fine currently thank you for asking.
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@muellerzr thanks a lot for your passion when teaching! 
I was watching your awesome video A walk with fastai2 - Tabular - Lesson 3 and I had a couple questions:
-
Why is your test dataloader using df.iloc[:100]. Arenāt these rows used for training already? Or was this choice done just for the sake of illustration of how ClassConfusion works?
-
When looking at the plots, in (<50K, >= 50K) the actual class was <50K and the predicted >=50K for the df.iloc[:100] that were wrongly classified. Is this statement correct? I just wanted to make sure.
- Where can I find reliable and understandable information for how fastai tabular embedding work? I understand how they are generated for NLP but to me this part is still very unclear for tabular data.
To everyone, any good courses you would recommend about explainability? I would like to learn more about how SHAP works and what the different plots mean.
Just for the sake of visualization 
Yup youāre correct!
See here, an article by Rachel back in 2018 (but nothingās changed 
)
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Hereās a Kaggle mini-series (I think thatās what itās called) that looks pretty good. Covers permutation importance along with SHAP and a few others:
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Thanks a lot! Quick doubt. How can I extract a row from here?
I tried learn.dls.valid_ds.iloc[800,:] as I would in pandas but I get TypeError: only list-like objects are allowed to be passed to isin(), you passed a [slice]. Note that type(learn.dls.valid_ds) is not dataframe but fastai2.tabular.core.TabularPandas
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Promise Iām not ignoring you Iāll be able to get back to you on this either Tuesday evening or Wednesday evening at the latest Apologies!
Also in regards to this week, Iām currently working on traveling home which will be on Wednesday when we would normally do class, so for everyoneās ease itāll be same time on Thursday. I appreciate your understanding and my apologies. Next week once we start NLP there shouldnāt be any issues whatsoever in terms of weird set backs thanks to covid (And those will be at our regular Wednesday time)
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