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  1. A public repo of datasets. Contribute to datasciencedojo/datasets development by creating an account on GitHub.

  2. gist.github.com › fyyying › 4aa5b471860321d7b47fd881898162b7titanic_dataset.csv · GitHub

    Apr 9, 2024 · Clone this repository at <script src="https://gist.github.com/fyyying/4aa5b471860321d7b47fd881898162b7.js"></script> Save fyyying/4aa5b471860321d7b47fd881898162b7 to your computer and use it in GitHub Desktop.

  3. 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”.

  4. The Titanic passengers data set. GitHub Gist: instantly share code, notes, and snippets.

  5. Aug 9, 2021 · The dataset consists of the information about people boarding the famous RMS Titanic. Various variables present in the dataset includes data of age, sex, fare, ticket etc. The dataset...

  6. Titanic Dataset. A classification task, predict whether or not passengers in the test set survived. This task is also an ongoing competition on the data science competition website Kaggle, so after making a prediction results can be submitted to the leaderboard.

  7. Analysis of Titanic Survival Data. Introduction ¶. The Titanic sank on April 15, 1912 during her maiden voyage. After colliding with an iceberg, 1502 of its 2224 passengers died. The data set investigated in the following sections contains detailed information about 891 passengers. The data can be found on Kaggle and be downloaded from there.

  8. gist.github.com › teamtom › 1af7b484954b2d4b7e981ea3e7a27f24titanic full dataset · GitHub

    titanic full dataset. Raw. titanic_full.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. pclass. survived. name. sex. age.

  9. Predict survival on the Titanic and get familiar with ML basics.

  10. Contribute to ansidaS/titanic development by creating an account on GitHub.