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Henry Forbes. Asplund, Master. Clarence Gustaf Hugo. Becker, Master. Richard F. Navratil, Master. Michel M. A public repo of datasets. Contribute to datasciencedojo/datasets development by creating an account on GitHub.
Contents. Titanic Dataset PPT.pptx: A PowerPoint presentation that details the analysis of the Titanic dataset. It includes steps such as data cleaning, exploratory data analysis, visualizations, and model building to predict survival outcomes based on various factors. Titanic IDS.ipynb: A Jupyter notebook containing the code for data cleaning ...
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Jul 31, 2024 · Raw. titanic_dataset.csv. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode characters. Show hidden characters. PassengerId.
This project explores the infamous Titanic dataset to uncover insights into the tragic sinking of the Titanic and predict survival outcomes of its passengers. Using Python and various data science libraries, the analysis encompasses data cleaning, exploratory data analysis (EDA), feature engineering, and predictive modeling.
Aug 29, 2014 · Dataset(titanic.txt), added in the repository. This dataset has passenger information who boarded the Titanic along with other information like survival status, Class, Fare, and other variables. The unfortunate event which was occurred on 15 April 1912, the Titanic sank after colliding with an iceberg, aboard 2224 peoples.
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.
An in-depth analysis of the Titanic dataset, exploring passenger demographics, survival rates, and other key metrics using Python. This repository contains code for data acquisition, preprocessing, visualization, and a detailed exploration of patterns and insights related to the tragic sinking of the RMS Titanic. Resources
Welcome to the Titanic Classification project repository! This project aims to predict whether a passenger on the Titanic survived or not based on various features such as age, gender, class, and more. python machine-learning prediction classification titanic-survival-prediction titanic-dataset. Updated Oct 4, 2023.
Data analysis is a statistical method used to describe variability among observed, correlated variables. The goal of performing factor analysis is to search for some unobserved variables called factors. This dataset has passenger information who boarded the Titanic along with other information like survival status, Class, Fare, and other variables.
