Titanic Passenger Survival Prediction using Machine Learning

A data analysis and machine learning project focused on preprocessing passenger data and training a predictive model using Logistic Regression on the Titanic dataset.

Key Features & Workflow:

- Data Cleaning & Preprocessing: Handled missing values and structured raw passenger features.

- Feature Encoding: Transformed categorical variables into numerical inputs suitable for machine learning algorithms.

- Model Training: Trained a Logistic Regression classifier to accurately predict survival outcomes.

- Model Evaluation: Evaluated model performance using accuracy metrics and confusion matrix analysis.

Technologies & Tools Used:

- Programming Language: Python

- Libraries: Pandas, NumPy, Scikit-Learn

- Environment: VS Code / Jupyter Notebook