Kaggle Project: Titanic Survival Prediction (ML model development and evaluation).
Built a Kaggle ML pipeline for Titanic survival prediction, involving data preprocessing steps such as feature extraction, encoding, and validation. Implemented engineered features including Title extraction and Age/Fare grouping to prepare inputs for model training. Used labeled outcomes (survival labels in the dataset) to train and evaluate a classifier using cross-validation and leaderboard scoring. • Engineered features (Title, FamilySize, Age/Fare grouping). • Trained and tuned a Random Forest Classifier with hyperparameter optimization. • Achieved 83.39% cross-validated accuracy. • Produced a Kaggle submission through preprocessing→encoding→validation workflow.
2025 - 2025