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Titanic: Machine Learning from Disaster

This repository has been created for a competition in Kaggle website.

Kaggle Test Score: 0.80861

Information about the competition:

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.

One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class.

In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.

For more information about the competition please click.

This repository includes:

  • A python file which includes some functions for data cleaning, creating new features, mapping and etc.
  • A python file which includes some functions for plotting graphs.
  • A jupyter notebook file to do machine learning !
  • Training and test datasets from Kaggle. For information about datasets click here.

How to use the repository:

  • All data munging operations is done by functions.py file. You can add, delete or change functions.
  • Then, use Titanic.ipynb file to use your python files and do your data munging, also to create a model and make submission.

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Repository for the competition "Titanic: Machine Learning from Disaster" on Kaggle.

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