Predicting Car Fuel Efficiency using Multiple Linear Regression

Stock Market Prediction Using Logistic Regression, Logistic Regression with Lasso Regularization, Random Forest, Support Vector Machines (SVM), Neural Networks (NN), XGBoost

Lung Cancer Prediction with Logistic Regression ,Decision Trees ,Random Forest,Support Vector Machines (SVM)

Predicting Breast Cancer with Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Logistic Regression, Random Forest, K-Nearest Neighbors (KNN), Neural Networks (NN)

Telco Customer Churn Prediction Using Logistic Regression, Decision Trees and Random Forests

Predicting Medical Insurance Premium Prices using Machine Learning Models Used: Forward Stepwise Linear Regression Principal Component Regression (PCR) with 5 components Principal Component Regression (PCR) with 9 components Random Forest Regression Gradient Boosting Regression Support Vector Machines (SVM) Decision Trees

Heart Failure Prediction Using Logistic Regression, Decision Tree, Random Forest,SVM,KNN,Gradient Boosting,Naive Bayes

Predicting Wine Quality Using Decision Tree, Random Forest, XGBoost, Naive Bayes, Gradient Boosting Regression (GBM), and Support Vector Machine (SVM) models.

Graduate Admissions Prediction with SVM and XGBoost

Predict credit risk using ML models for loan applicants. Evaluate logistic regression, kNN, random forest, and XGBoost. Choose XGBoost for its high accuracy and sensitivity. Improve lending decisions and minimize defaults.