Baseball Salary Prediction Using Regularization Techniques

Technologies: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn Project Summary Developed a machine learning regression model to predict Major League Baseball player salaries using statistical performance data. Applied regularization techniques to improve prediction accuracy, reduce overfitting, and identify the most influential factors affecting player salaries. Key Responsibilities Collected and preprocessed a dataset of 263 MLB players with 19 performance-related features and handled missing salary values. Performed exploratory data analysis using correlation matrices, histograms, scatter plots, and descriptive statistics to identify trends and relationships. Built and evaluated Linear Regression, Ridge Regression, Lasso Regression, and Recursive Feature Elimination (RFE) models for salary prediction. Applied feature scaling (standardization and normalization) and 10-fold cross-validation to improve model stability and evaluate performance. Identified key salary predictors including Career Runs, Career Hits, Career At-Bats, Career RBIs, and Career Walks, improving model interpretability through regularization. Compared model performance using R² scores and analyzed the impact of Ridge and Lasso regularization on feature selection and multicollinearity.

Titanic Survival Prediction

Tools: Python, Pandas, NumPy, Scikit-learn, Matplotlib Built a machine learning model to predict passenger survival on the Titanic dataset. Cleaned missing data, performed exploratory data analysis, engineered new features such as family size and title, and compared multiple classification models including Logistic Regression, Random Forest, SVM, and Gradient Boosting. Tuned hyperparameters and evaluated model performance using cross-validation and Kaggle submissions.

INSCAPE BUILDERS AND CONTRACTORS

Inscape Builders was a full-stack web development project where I gathered requirements, planned the website structure, created wireframes, designed the user interface, and developed a responsive business website using HTML, CSS, and JavaScript. I built pages showcasing the company's services, projects, and contact information, tested the site across devices and browsers, optimized performance and usability, and completed the project through deployment, delivering a professional, user-friendly website from concept to launch.