Titanic Survival Prediction Using Machine Learning

This project focuses on predicting passenger survival on the Titanic using machine learning classification algorithms. The dataset includes features such as age, gender, passenger class, fare, and family size.

In this project, the data was cleaned and preprocessed using Python libraries such as Pandas and NumPy. The dataset was then divided into training and testing sets to build predictive models.

Different classification algorithms were applied and evaluated using metrics such as Accuracy, Precision, Recall, F1-Score, and Confusion Matrix. The goal of the project was to determine which model provides the most accurate prediction of survival.

Technologies used:

Python

Pandas

NumPy

Scikit-learn