🎯 Predict visa approval outcomes using machine learning, enhancing decision-making and efficiency for immigration professionals based on applicant data.

This project builds a predictive model to estimate visa approval likelihood using candidate and job-related features. It showcases an end-to-end machine learning workflow with EDA, feature engineering, and model tuning to automate parts of the visa evaluation process.

Apply machine learning techniques to predict visa application approval outcomes based on applicant demographics, education, job experience, and employment-related attributes. The objective is to support more consistent, data-driven certification decisions by identifying key approval drivers and high-risk cases early in the process.