Handling missing data | Numerical Data | Simple Imputer
Channel: CampusX
Date: 2021-04-23

Simple Imputer is a practical solution for filling missing numerical values in a dataset. This method replaces missing entries with the mean, median, or a specified constant, providing a straightforward approach to address and mitigate the impact of missing numerical data in your dataset.

Code Used: https://github.com/campusx-official/100-days-of-machine-learning/upload/main/day36-imputing-numerical-data

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⌚Time Stamps⌚

00:00 - Intro
00:37 - Handling Missing Numerical Data
03:33 - Mean / Median Imputation
07:55 - Code Demo
17:15 - Imputation using SKlearn
20:15 - Arbitarry Value Imputation
22:40 - Code Demo
25:57 - End of Distribution Imputation
30:09 - Outro