Building a Titanic Survival Prediction Model Using Pipelines in Scikit-Learn Predicting Titanic survival is a classic data science problem, and in this project, we aim to create a streamlined machine learning pipeline using Python's Scikit-Learn library. This project covers the essential steps involved in data preprocessing, feature engineering, and model training. Project Overview The goal of this project is to predict whether a passenger survived the Titanic disaster using machine learning techniques. The dataset is sourced from Kaggle's Titanic competition and consists of passenger details such as class, age, gender, and more. We utilize various Scikit-Learn tools to create an efficient and reproducible machine learning pipeline. Step-by-Step Process 1. Data Preprocessing We start by…