Bank Marketing Data Analysis Project

Project Overview

<table><tbody><tr><td data-start=\"6425\" data-end=\"6456\" data-col-size=\"sm\"><strong data-start=\"6427\" data-end=\"6442\"></strong></td></tr></tbody></table><table><tbody><tr><td data-start=\"6456\" data-end=\"7096\" data-col-size=\"xl\">The notebook begins by loading the “bank.csv” dataset (semicolon-delimited) into pandas and displaying its first few rows . It proceeds with exploratory data analysis—visualizations and mermaid diagrams for workflow documentation—then preprocesses features (e.g. encoding categorical variables), splits into train/test sets, and applies classification algorithms (e.g., Logistic Regression, Random Forest), evaluating via accuracy, confusion matrices, and classification reports.</td></tr></tbody></table>