Feature Encoding in ML: Label & One-Hot with Python

In this video, we explore the fundamentals of feature encoding, a key step in preparing categorical data for machine learning models. Specifically, we break down:

📌 Topics Covered:

What is Feature Encoding?

Label Encoding: How it works and when to use it

One-Hot Encoding: Benefits and use cases

Key differences and when to choose which

Common mistakes and how to avoid them

💻 Notebook Demo Included
This tutorial includes a step-by-step Python notebook walkthrough, demonstrating both encoding techniques using real datasets and tools like pandas and scikit-learn.

🔗 Notebook: https://github.com/mdkamrulhasan/machine_learning_concepts/blob/master/notebooks/supervised/Regression_diabetes_LR_kNN_DTree.ipynb

🐙 GitHub Repo: https://github.com/mdkamrulhasan/machine_learning_concepts/blob/master/notebooks/supervised/Regression_diabetes_LR_kNN_DTree.ipynb