Machine Learning - Handling Categorical Data

In this video, we are going to learn about how to handle Categorical data in machine learning. It’s difficult to create ML models that can’t have features that have categorical values, such models cannot function. It is usually a fixed number of possible values with assigning each individual observation to a particular group on the basis of some qualitative. While learning Handling Categorical Data, we will explain different techniques Label and One hot encoding methods. Also, we will see what is the drawback of both techniques. Learn more: https://www.geeksforgeeks.org/exploring-categorical-data/ 

https://www.geeksforgeeks.org/ml-one-hot-encoding-of-datasets-in-python/ 

https://www.geeksforgeeks.org/how-to-convert-categorical-features-to-numerical-features-in-python/

https://www.geeksforgeeks.org/how-to-convert-categorical-string-data-into-numeric-in-python/