GitHub - tanercam/Salary-Prediction-Project-of-US-Baseball-Major-League-Players-with-Thirteen-Different-Machine-Learni: In this project, thirteen different machine learning models were employed to predict salary of any US Major Baseball League player. These are Linear Regression, Ridge Regression, Lasso Regression, ElasticNet Regression, KNN (K-Nearest Neighbors), SVR (Support Vector Regression), MLP (Multilayer Perceptron), CART (Classification and Regression Trees), Random Forests, GBM (Gradient Boosting Machines), XGBoost (Extreme Gradient Boosting), LightGBM, and CatBoost (Category Boosting) Machine Learning Models.

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In this project, thirteen different machine learning models were employed to predict salary of any US Major Baseball League player. These are Linear Regression, Ridge Regression, Lasso Regression, ElasticNet Regression, KNN (K-Nearest Neighbors), SVR (Support Vector Regression), MLP (Multilayer Perceptron), CART (Classification and Regression Tr…