This project aims to predict whether a person survived or not on the Titanic using machine learning. It utilizes the RandomForestClassifier from scikit-learn to build a classification model.

• Titanic Classification.ipynb: Jupyter Notebook containing the code for data loading, preprocessing, model training, and evaluation.
• README.md: Documentation providing an overview of the project and instructions.

Make sure you have the following dependencies installed:

• pandas
• scikit-learn

Install dependencies using:

pip install pandas scikit-learn

1. Open the Titanic Classification.ipynb notebook in a Jupyter environment.
2. Run each cell sequentially to execute the code.
3. The notebook will output the accuracy of the trained model on the test set.

The dataset used for training and testing the model is the Titanic dataset, available at this URL. The dataset contains information about passengers, including whether they survived, age, gender, etc.

The classification model used is a RandomForestClassifier from scikit-learn with 100 trees and a random state for reproducibility.