Data Pre-processing

I’ve recently created an interactive notebook that summarizes everything you need to know about data preprocessing using Python — presented in a practical and easy-to-apply style.

What will you learn inside?

? This notebook walks you step by step through how to prepare your data before training any model, with a clear and simple process:

Exploring the data (EDA) to understand its patterns and distributions

Cleaning the data and removing noise

Smart handling of missing values

Text encoding (Label Encoding)

Splitting the data into training and testing sets

Feature scaling to enhance model performance

Using tools like Pandas and Scikit-learn