?? Day15 of #100DaysOfPython ??
Surya Singh
Sr. AI/ML Consultant & Team Lead @Accenture Strategy | ex-ZS, EY | MS in ML & AI
Today, we're diving into different types of techniques for handling missing values in a dataset!
Q. What are the different types of techniques for handling missing data?
In today's article we will start with -
1. Imputing missing values with mean/median/mode:
Let's dive deeper with an example below:
Imputing feature with mean/median/mode can have the following:
Advantages:
Disadvantages:
What real world examples can you think of where imputing missing data in feature with mean/median/mode would be a better choice?