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The classic titanic survival with machine learning
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Machine Learning Engineer Nanodegree

Introduction and Foundations

Project: Titanic Survival Exploration


This project requires Python and the following Python libraries installed:

You will also need to have software installed to run and execute a Jupyter Notebook

If you do not have Python installed yet, it is highly recommended that you install the Anaconda distribution of Python, which already has the above packages and more included


Template code is provided in the notebook titanic_survival_exploration.ipynb notebook file. Additional supporting code can be found in While some code has already been implemented to get you started, you will need to implement additional functionality when requested to successfully complete the project. Note that the code included in is meant to be used out-of-the-box and not intended for students to manipulate. If you are interested in how the visualizations are created in the notebook, please feel free to explore this Python file.


In a terminal or command window, navigate to the top-level project directory titanic_survival_exploration/ (that contains this README) and run one of the following commands:

jupyter notebook titanic_survival_exploration.ipynb


ipython notebook titanic_survival_exploration.ipynb

This will open the Jupyter Notebook software and project file in your web browser.


The dataset used in this project is included as titanic_data.csv. This dataset is provided by Udacity and contains the following attributes:


  • pclass : Passenger Class (1 = 1st; 2 = 2nd; 3 = 3rd)
  • name : Name
  • sex : Sex
  • age : Age
  • sibsp : Number of Siblings/Spouses Aboard
  • parch : Number of Parents/Children Aboard
  • ticket : Ticket Number
  • fare : Passenger Fare
  • cabin : Cabin
  • embarked : Port of Embarkation (C = Cherbourg; Q = Queenstown; S = Southampton)

Target Variable

  • survival : Survival (0 = No; 1 = Yes)
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