manmeet2341 / kaggle-titanic

Predicting the survival of passengers in the testing data.

Kaggle-Titanic

This project uses the training dataset to train a ML model to predict the survival of passengers in testing dataset. Both datasets are available at Kaggle Titanic.

Contents

• train.csv: To train the data
• test.csv: To test the data and predict the outcome
• final.csv: Final outcome to be submitted
• Titanic.ipynb: Jupyter notebook for predicting survival
• Titanic_Unsupervised.ipynb: Predicting survival using unsupervised machine learning (K-means)

Dataset

• PassengerId: Id of the passenger
• Survived: Survival of the passenger (0 = No, 1 = Yes)
• Pclass: Ticket class (1 = 1st, 2 = 2nd, 3 = 3rd)
• Name: Name
• Sex: Sex
• Age: Age in years
• SibSp: Number of siblings / spouses aboard the Titanic
• Parch: Number of parents / children aboard the Titanic
• Ticket: Ticket number
• Fare: Passenger fare
• Cabin: Cabin number
• Embarked: Port of Embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)

Objective

To use machine learning to create a model that predicts which passengers survived the Titanic shipwreck.

Purpose

The purpose of this project was to gain an introductory exposure to Machine Learning Classification concepts along with data visualization. The project makes use of Scikit-Learn, Pandas and Data Visualization(Matplotlib and Seaborn) Libraries.

My score

0.74880