This repository contains an implementation of Titanic Survival Model with decision trees in python.

Overview

In this repository, we demonstrate how to perform decision trees and data manipulation using Python to predict a Titanic survival model. We utilize libraries such as NumPy, pandas, and scikit-learn to implement and visualize the decision trees model. Additionally, we provide a simple example along with explanations to help you understand how to apply decision trees to your own datasets.

Requirements

To run the code in the Jupyter Notebook, you need to have Python installed on your system along with the following libraries:

• NumPy
• pandas
• scikit-learn

You can install these libraries using pip:

pip install numpy pandas scikit-learn 

Usage

1. Clone this repository to your local machine:

git clone https://github.com/BaraSedih11/Titanic-Survival-Model.git

2. Navigate to the repository directory:

cd Titanic

3. Open and run the Jupyter Notebook titanic_survival_exploration.ipynb using Jupyter Notebook or JupyterLab.

4. Follow along with the code and comments in the notebook to understand how decision trees is implemented using Python.

Acknowledgements

• scikit-learn: The scikit-learn library for machine learning in Python.
• NumPy: The NumPy library for numerical computing in Python.
• pandas: The pandas library for data manipulation and analysis in Python.