This is a guided project from 365datascience.com. It provided instructions on what to do but did not provide the code.
The Case Description from the project:
Background: In a machine learning classification problem, the algorithm assigns labels to instances based on their features. This Machine Learning for User Classification project will allow you to apply this technique by utilizing an excerpt of our own data stripped of personally identifiable information. You will examine student engagement metrics, such as the number of days students have spent on the platform, the minutes of watched content, and the number of courses they’ve started. You’ll then use this data to train several machine learning models, including logistic regression, k-nearest neighbors, support vector machines, decision trees, and random forests. The aim is to predict whether students would upgrade their free plan to a paid one.
Business Objective: Such an analysis is of utmost importance not only for 365 but for any online company. Predicting potential customers can be used for advertisement targeting or reaching out with exclusive offers. This helps allocate a budget for users likely to benefit from the product, aiming to increase the company’s revenue.