This project implements an advanced football match result prediction system using Machine Learning algorithms
Random Forest Classifier for Customer Churn Prediction
Developed an ensemble ML classification model to predict U.S. visa case outcomes (Certified vs Denied) using applicant and employer attributes. Performed EDA, sampling, and model tuning (Random Forest, Gradient Boosting, XGBoost) to improve decision efficiency and identify key policy drivers like education, experience, and wage trends.
SVM hyperparameter tuning on the Iris dataset using GridSearchCV and RandomizedSearchCV with cross-validation.
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