Coding Challenge: Supervised Learning
Explore how to apply supervised learning techniques by selecting relevant features and using classification algorithms to predict customer churn. Learn to build multiple models and combine them through ensemble methods to improve prediction accuracy and compare predicted outcomes to actual data.
We'll cover the following...
We'll cover the following...
We’ll now work with a dataset containing information on a bank’s customer base, containing 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) that ...