Titanic End-to-End Feature Engineering & Data Preprocessing

Overview

This project focuses on end-to-end feature engineering and data preprocessing for the Titanic dataset. The goal is to prepare the data for machine learning models by handling various types of features and transforming the dataset accordingly.

Project Structure

1. Data Exploration: Initial exploration of the Titanic dataset to understand its structure and the types of features available.
2. Feature Engineering: Creation of new features and modification of existing ones to enhance the dataset.
3. Data Preprocessing: Handling missing values, encoding categorical variables, and scaling numerical features.

Getting Started

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.x
• Pandas
• NumPy
• Scikit-learn
• Seaborn (for data visualization)

You can install the necessary Python packages using:

pip install pandas numpy scikit-learn seaborn