This repository contains the code and resources for a machine learning project focused on predicting the survival of passengers aboard the RMS Titanic. The project is based on the famous Titanic dataset, which includes various features such as passenger demographics, ticket information, and socio-economic status.
Project Overview The Titanic disaster is one of history's most infamous shipwrecks. On April 15, 1912, the RMS Titanic sank after colliding with an iceberg, resulting in the tragic loss of over 1,500 lives. This project aims to build a predictive model to answer the question: "What kinds of people were more likely to survive?"
Key Features Data Preprocessing: Handling missing values, feature engineering, and data normalization. Modeling: Implemented various machine learning algorithms, including Logistic Regression, Decision Trees, and Random Forest. Evaluation: Model performance was evaluated using accuracy and other relevant metrics. Visualization: Key insights were visualized to highlight factors that influenced survival rates. Getting Started To run the code in this repository, clone the repository and install the necessary dependencies listed in the requirements.txt file. The project is implemented in Python and uses libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.