Project - Predicting Titanic Passenger Survival using Machine Learning and Python

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Titanic Machine Learning Project - About the dataset

Welcome to the Titanic dataset project.

INSTRUCTIONS

The goal is to predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and so on.

The dataset is available on Kaggle as a part of their legendary Titanic ML competition. The dataset is available from the below link:

https://www.kaggle.com/c/titanic/data

Here is a quick explanation of some of the features:

  1. Survived: that's the target, 0 means the passenger did not survive, while 1 means he/she survived.
  2. Pclass: passenger class.
  3. Name, Sex, Age: self-explanatory
  4. SibSp: how many siblings & spouses of the passenger aboard the Titanic.
  5. Parch: how many children & parents of the passenger aboard the Titanic.
  6. Ticket: ticket id Fare: price paid (in pounds)
  7. Cabin: passenger's cabin number
  8. Embarked: where the passenger embarked the Titanic

The dataset is split into 2 parts, train.csv and test.csv for training and testing your Machine Learning models respectively.


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