Outlier Detection and Removal using Z-score Method | Handling Outliers Part 2
Channel: CampusX
Date: 2021-04-30

The Z-score method identifies outliers by measuring how far each data point is from the mean in terms of standard deviations. Points beyond a certain Z-score threshold are considered outliers. By applying this method, we can effectively detect and remove outliers, enhancing the robustness of our data analysis.

Code Used: https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day42-outlier-removal-using-zscore

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⌚Time Stamps⌚

00:00 - Intro
00:30 - Outlier removal using Z score
03:40 - Z Score Formula
05:07 - Outlier Treatment
08:00 - Code Demo
14:08 - Capping