Python Machine Learning Tutorial | Handling Missing Data | Databytes

Published: 19 May 2022
on channel: DataCamp

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This machine learning tutorial will take you through the different ways of dealing with missing data when building machine learning models in Python. The topics covered in this video are:

00:00 - 04:07 Missing data theory
04:08 - 06:50 Msleep data set
06:51 - 09:08 Standardizing missing data
09:09 - 10:01 Quantifying missing data
10:02 - 10:51 Dropping missing data
10:52 - 13:11 Separating data by column type
13:12 - 18:03 Replacing with mean or median
18:04 - 19:57 Replacing with mode
19:58 - 22:31 Iterative methods to find values
22:32 - 23:10 Next steps

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