Data Preparation for Machine Learning: Categorical and Numerical Data

This lecture covers the preparation of data for machine learning algorithms, focusing on handling numerical and categorical data. It explains the process of converting categorical data into numerical form, emphasizing the importance of proper data handling. The instructor demonstrates techniques to transform categorical data into numerical indexes and provides guidance on writing functions for data conversion. Additionally, the lecture delves into the significance of data visualization in understanding patterns and relationships within datasets, showcasing methods to visualize data features effectively through pairwise plotting and histograms.