Data Preprocessing

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Are the Data-Preprocessing techniques provided here sufficient for most of the (real)datasets? Or an external reading is required? :thinking:

Hey @gpk2000, great question! We didn’t explain the whole data preprocessing since we are focusing on deep learning :wink: While you are interested to data preprocessing, here is a great resource:


Thank you for the reply. I will look into it. :+1:

While executing this snippet:
inputs = inputs.fillna(inputs.mean())

Getting warning:
/tmp/ipykernel_7756/ FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction. inputs.fillna(inputs.mean())

As solution I would suggest to add these parameters:
inputs.mean(skipna=True, numeric_only=True)

More info about mean function here

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inputs, outputs = data.iloc[:, 0:2], data.iloc[:, 2]
inputs = inputs.fillna(inputs.mean((skipna=True, numeric_only=True)))

File “”, line 2
inputs = inputs.fillna(inputs.mean((skipna=True, numeric_only=True)))
SyntaxError: invalid syntax

Hi khushboo! You can try
inputs = inputs.fillna(inputs.mean(skipna=True, numeric_only=True))
instead of
inputs = inputs.fillna(inputs.mean((skipna=True, numeric_only=True)))
There are too much parentheses

Thank you to help me solve the problem!!