Data Scrubbing Operation: One-Hot Encoding
Explore the process of one-hot encoding to convert categorical variables into a format suitable for machine learning models. Understand how this technique expands datasets by creating binary columns and learn to optimize dataframes by removing redundant columns using parameters like drop_first. This lesson helps you prepare categorical data effectively for algorithms that require numeric input.
We'll cover the following...
We'll cover the following...
Quick overview
In data science, it’s common to have a mismatch or compatibility issue between the data and the algorithm. While the variable’s contents might be relevant, the algorithm might not read the data in its default form. Text-based categorical values, for example, can’t be parsed and mathematically modeled ...