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Description
key things to highlight:
- wrangle each supported datatype (include use of loaded-in object + filename of saved object):
- dataframe
- array
- text-- use a few different scikit-learn models (train with different built-in and hugging-face corpora) and also show a few hugging-face models. also demo vectorization (scikit-learn) vs. embedding using an already-trained model
- image
- mixed list of several datatypes
- interpolation and imputation
- decorators:
- list_generalizer, funnel
- stacking and unstacking (show examples of how this is useful); also show stack_apply/unstack_apply
- io:
- loading data (local + remote)
- saving data
- util:
- btwn
- dataframe_like, array_like
- load_dataframe (show demos with a few different filetypes-- e.g. csv, json, etc. to show how extensions are handled automatically)
- core:
- show how config.ini is set up and how it can be customized
- show how get_default_options and apply_default_options work
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