• Using Machine Learning to Classify Students and Predict Student Purchases

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:

1. logistic regression
2. k-nearest neighbors
3. support vector machines
4. decision trees
5. random forests The aim is to predict whether students would upgrade their free plan to a paid one.

• You’ll need to prepare the following libraries:

. pandas . matplotlib . statsmodels . scikit-learn . numpy . seaborn

https://learn.365datascience.com/projects/machine-learning-for-user-classification/