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Data is not flat

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Data is not flat
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How can feature engineering help?
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132
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CC Attribution - NonCommercial - ShareAlike 3.0 Unported:
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Abstract
Feature engineering and model training often comes hand in hand. Some tasks have an overwhelming amount of high dimensional data, some tasks have little data or very low-dimension data. This talk targets the latter problem: what can be done with the data itself to significantly improve the model performance and when manual feature engineering does make sense. A sample case of Classification problem with NN will be presented The goal of the talk is to remind about something every person working with the data thinks and probably uses.