Titanic Classification: Employ machine learning to predict passenger survival on the Titanic. Analyze passenger attributes using algorithms, gaining insights into factors affecting survival rates in this iconic disaster.
Welcome to the Titanic Survival Prediction System repository. This project focuses on developing a predictive model to determine whether a person would have survived the Titanic disaster. By analyzing a range of factors, including socio-economic status, age, gender, and more, this system sheds light on the key attributes influencing survival outcomes.
Utilizes machine learning algorithms and data preprocessing techniques. Processes Titanic dataset to create a comprehensive analysis pipeline. Implements classification models to predict survival probability. Identifies and visualizes significant factors affecting survival. Offers interactive exploration of data insights through Jupyter notebooks. Promotes understanding of feature importance in survival prediction.
Clone the repository: git clone https://github.com/yourusername/titanic-survival-prediction.git Install required packages: pip install -r requirements.txt Explore Jupyter notebooks for data preprocessing, model training, and analysis. Customize model parameters and experiment with alternative algorithms. Engage with visualizations to comprehend feature impact on survival.
Contributions are encouraged! Fork the repository, make enhancements, and create pull requests to contribute to this impactful project.
While this project provides insights into potential survival outcomes based on historical data, it's for educational purposes. Actual survival during the Titanic disaster was influenced by a range of circumstances, and this model's predictions may not reflect real-world scenarios accurately.