🚢 Titanic Survival Prediction Project

This project is a machine learning solution to the famous Titanic dataset, where the goal is to predict which passengers survived the tragedy based on features like age, class, gender, and more.

📊 Project Overview

Using Python and common data science libraries, this notebook walks through the full data science workflow:

• Data cleaning and preprocessing
• Exploratory data analysis (EDA)
• Feature engineering
• Model training and evaluation

🧰 Tools & Libraries Used

• pandas for data manipulation
• matplotlib & seaborn for visualizations
• scikit-learn for building ML models
• Jupyter Notebook for code and documentation

📁 Files

• Titanic_Project.ipynb — Main notebook with full analysis and modeling
• train.csv — Training dataset (from Kaggle Titanic Challenge)
• test.csv — (Optional) Test dataset for final predictions
• README.md — Project documentation (this file)

🧠 Key Concepts Covered

• Handling missing values
• Label encoding and feature selection
• Logistic Regression, Decision Tree, Random Forest
• Model accuracy and confusion matrix
• Feature importance analysis

📌 How to Run

1. Clone the repo:

   git clone https://github.com/Hardikk-7/Titanic-Project.git
   cd Titanic-Project