Coding Challenge: Preprocessing
Explore preprocessing methods such as imputing missing values, encoding categorical features, scaling numeric data, and discretizing continuous variables using scikit-learn. This lesson guides you through preparing a dataset by applying these techniques to ensure clean, normalized, and fully numeric data ready for machine learning.
We'll cover the following...
Now we’ll work with a dataset containing information about a bank’s customer base, featuring the following variables:
customerID: The customer’s unique ID.gender: The customer’s gender.SeniorCitizen: The customer’s senior citizen status.Partner: The customer’s relationship status.Dependents: The customer’s number of dependents?tenure: The length of time (in months) the the individual has been a customer.Services that the ...