E-commerce Purchase Probability Prediction

Machine Learning Project

From online traffic information given by a retailer, it was possible to observe who are the customers, and their purchase habits (if the user purchase or not, the time spent before purchasing, products visited, etc). With this information, it is intended to predict the purchase probability, so the retailer can understand their customers’ behavior to perform better on sales. The models applied for prediction were Logistic Regression and Naïve Bayes.

Language: Python | Libraries: Numpy, Pandas, Matplotlib, Sklearn