Handling Categorical Data in Machine Learning: Easy Explanation for Data Science Interviews

Handling categorical data in machine learning projects is a very common topic in data science interviews. In this video, I’ll cover the difference between treating a variable as a dummy variable vs. a non-dummy variable, how you can deal with categorical features when the number of levels is very large, and the pros and cons of various strategies.

Feature hashing
https://en.wikipedia.org/wiki/Feature_hashing


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Contents of this video:
====================
00:00 Introduction
00:48 Categorical Data
02:22 Ordinal Features & Class Labels
03:38 One-Hot Encoding
05:32 Dummy Encoding
06:30 Problems of One-Hot & Dummy Encoding
07:26 Feature Hashing