Comparing Label Encoding And One-Hot Encoding With Python Implementation

As machine learning algorithms most often accept only numerical inputs, it is important to encode the categorical variables into some specific numerical values. In this article, we compare the label encoding and one-hot encoding techniques by implementing it in Python. Label Encoding Label encoding is one of the popular processes of converting labels into numeric values in order to make it understandable for machines. For instance, if we have a column of level in a dataset which includes beginners, intermediate and advanced. After applying the label encoder, it will be converted into 0,1 and 2 respectively.  OneHot Encoding One-Hot Encoding is one of the most widely used encoding methods in ML models. This technique is used to quantify categorical data where it compares each level of