Search results
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.
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.
Titanic Dataset Analysis. Overview This project focuses on downloading, analyzing, and visualizing the famous Titanic dataset. This dataset contains information about the passengers aboard the RMS Titanic, which tragically sank on its maiden voyage. It includes data such as age, fare, class, and whether the passenger survived or not. Workflow
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 ...
The Titanic Data Science Project seeks to predict passenger survival outcomes from the infamous 1912 disaster using machine learning. Our goal is to identify key survival determinants by analyzing a dataset that includes age, gender, class, and fare, among other variables.
Saved searches Use saved searches to filter your results more quickly
Welcome to the captivating world of Titanic dataset analysis! This repository serves as your gateway to exploring the rich insights hidden within the Titanic dataset using Python and Kaggle. Delve deep into the realm of classification techniques and machine learning algorithms
Explore the Titanic dataset, understand the features, and define the target variable. Identify and handle missing values, outliers, and inconsistencies in the dataset. Exploratory Data Analysis (EDA): Analyze and visualize the dataset to understand relationships between features. Identify missing values, outliers, and correlations. Data ...
Titanic Dataset - Train.csv will contain the details of a subset of the passengers on board (891 to be exact) and importantly, will reveal whether they survived or not, also known as the “ground truth”. The `test.csv` dataset contains similar information but does not disclose the “ground truth” for each passenger.
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.
