Python for Deep Learning - Build Neural Networks in Python - One-hot encoding using scikit-learn

The video tutorial explains how to use the column transformer and one hot encoder from sklearn to transform categorical data into numerical data. It covers the importation of necessary libraries, the creation of a column transformer object, and the specification of parameters such as transformers and remainder. The tutorial provides a step-by-step guide on implementing the column transformer with code examples, including fitting and transforming a dataset. It concludes with an interpretation of the output, explaining how categorical data is converted into numerical data using one hot encoding.

How does the code handle the first index when transforming the data set?

What does the output of the one hot encoding represent in terms of geographical locations?

What are the next steps after transforming the data set with one hot encoding?