Data Cleaning & Transformation in Machine Learning 🧹🤖

This guide explores data cleaning and transformation, detailing their significance in machine learning. It addresses challenges like missing data and outliers, presents techniques such as imputation and normalisation, and highlights their role in improving model accuracy. Best practices and resources for further learning are also included.