Modelling #1
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Modelling #1
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The main purpose of this PR is to add
modelling.ipynb.This notebook demonstrates how to make a text classification model in
KerasandTensorflow.I use the
amazon_cells_labelled.txtdata source and achieve a test accuracy of 81% 🚀 .I also update
extract.ipynbso it no longer loads returns onepd.DataFramefor all three raw data sources.This notebook has been changed to return a single
pd.DataFramefor one data source.When training models on the combined data sources, accuracy was no better than chance. It's likely that sentiment is a domain specific problem and we can't train a single sentiment model (that's performant!) on multiple disparate data sources.