Encoding Label to One-Hot

Introduction

In this project, you will learn how to perform one-hot encoding on label data for a single-label classification task. One-hot encoding is a common technique used to transform categorical variables into a format that can be used by machine learning algorithms.

🎯 Tasks

In this project, you will learn:

• How to understand the concept of one-hot encoding and its importance in machine learning.
• How to implement a function to perform one-hot encoding on a list of sample labels.
• How to test the label encoding function with sample data.

🏆 Achievements

After completing this project, you will be able to:

• Transform categorical labels into a numerical format suitable for machine learning models.
• Understand the importance of data preprocessing and feature engineering in the machine learning pipeline.
• Demonstrate practical coding skills in Python to manipulate and transform data for machine learning tasks.