This article is a Python copying activity record of Chapter 9, Part 3: 'Logistic Regression Model' from the book 'Introduction to Data Analysis with Bayesian Statistical Modeling using R and Stan'.

"Last time we predicted 'what tomorrow's sales will be,' but this time I want to predict 'whether this customer will buy a new product or not.' Sending direct mail (DM) to everyone is costly, so I ...

insurance-purchase-prediction 🚀 Insurance Purchase Prediction using Logistic Regression. This project applies binary classification to predict whether a customer will buy insurance based on age and ...

Churn prediction model built with Logistic Regression and Random Forest on 10,000 bank customer records. Random Forest achieved 86% accuracy. Age was the strongest churn predictor, and customers with ...