Titanic Data Analysis

Code and documentation for Kaggle's Titanic Data Analysis competition. The objective of this theme is to predict passenger survival based on various characteristics such as age, gender, class, etc.

Table of Contents.

• Overview
• Dataset
• Introduction
• Assumptions
• How to use
• Result

Overview

The Titanic dataset is a well-known dataset used in machine learning and data science for binary classification tasks. It includes data cleaning, feature engineering, model training and evaluation.

Dataset

The dataset used in this project can be found on Kaggle's Titanic competition page. It contains the following two files:

• train.csv: training dataset with features and labels.
• test.csv: test dataset containing unlabeled features.

Introduction

Open the Google Colab notebook from the following link:

[Google Colab: Titanic Analysis](https://colab.research.google.com/drive/1OFEXDtTRPVtXK8UIsFeNdn6rDnfWcuU2?hl=ja#scrollTo= moInQjCctBCz)

Prerequisites

You will need

• Google account
• Kaggle account (to access the dataset)

How to use

1. click on the Google Colab link above to open the notebook 2. download the dataset from Kaggle and upload it to Google Colab Download the dataset from Kaggle and upload it to Google Colab. Specific instructions are provided in the notebook. 3.
2. run the cells in the notebook in sequence to analyze the data.

Results

The results of the analysis, model performance evaluation and visualization are included within the Google Colab notebook.