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Update evalml docs to mention woodwork #1361

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merged 5 commits into from Oct 29, 2020
Merged

Update evalml docs to mention woodwork #1361

merged 5 commits into from Oct 29, 2020

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dsherry
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@dsherry dsherry commented Oct 28, 2020

Fix #1287

Adds a mention and example to the start page and to the automl user guide page about woodwork.

This is just to start us off. Eventually I'd like us to add a page or section to the automl guide about "formatting data for automl", which shows how to set the column types using woodwork, override some of the default inference and run automl with those settings.

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codecov bot commented Oct 28, 2020

Codecov Report

Merging #1361 into main will not change coverage.
The diff coverage is n/a.

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@@           Coverage Diff           @@
##             main    #1361   +/-   ##
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  Coverage   99.95%   99.95%           
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  Files         213      213           
  Lines       13857    13857           
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  Hits        13850    13850           
  Misses          7        7           

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dsherry commented Oct 29, 2020

Docs visible here for the start page

"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
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Oops, will delete this

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lgtm!

docs/source/start.ipynb Outdated Show resolved Hide resolved
docs/source/user_guide/automl.ipynb Outdated Show resolved Hide resolved
"source": [
"To provide data to EvalML, it is recommended that you create a `DataTable` object using [the woodwork project](https://woodwork.alteryx.com/en/stable/).\n",
"\n",
"EvalML also accepts and works well with pandas `DataFrames`. But using the `DataTable` makes it easy to control how EvalML will treat each feature, as a numeric feature, a categorical feature, a text feature or other type of feature. Woodwork `DataTable`s include features like inferring when a categorical feature should be treated as a text feature. For this reason, if you don't provide woodwork objects, EvalML will raise a warning."
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Suggested change
"EvalML also accepts and works well with pandas `DataFrames`. But using the `DataTable` makes it easy to control how EvalML will treat each feature, as a numeric feature, a categorical feature, a text feature or other type of feature. Woodwork `DataTable`s include features like inferring when a categorical feature should be treated as a text feature. For this reason, if you don't provide woodwork objects, EvalML will raise a warning."
"EvalML also accepts and works well with pandas `DataFrames`. But using the `DataTable` makes it easy to control how EvalML will treat each feature, as a numeric feature, a categorical feature, a text feature or other type of feature. Woodwork's DataTable includes features like inferring when a categorical feature should be treated as a natural language feature. For this reason, if you don't provide woodwork objects, EvalML will raise a warning."

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@gsheni ah right. I think we're gonna stick with "text" in evalml for the time being. Some of our classes use "text". We can have a separate conversation about that if you'd like.

I'll add in your other suggestion.

Thanks!

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gsheni
gsheni previously approved these changes Oct 29, 2020
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gsheni commented Oct 29, 2020

@dsherry Formating
Screen Shot 2020-10-29 at 1 08 21 PM

@gsheni gsheni self-requested a review October 29, 2020 17:09
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@gsheni gsheni dismissed their stale review October 29, 2020 17:10

re-reviewed and found some things.

@dsherry dsherry merged commit 77ae097 into main Oct 29, 2020
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@dsherry dsherry deleted the ds_1287_woodwork_docs branch October 29, 2020 17:32
@dsherry dsherry mentioned this pull request Oct 29, 2020
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Add documentation for Woodwork support
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