This Project is building a machine learning model that can predict whether a passenger survived in the Titanic incident or not. The complete project is done in R language. ggplot has been used for visualisation. After performing some feature engineering and feature selection we finally trained a Random Forest model and showed that how cross-validation technique can increase the accuracy of the model in prediction. We have performed 10 fold cross validation. For feature selection we tried with various logical combinations and connections between different features and checked the accuracy of the model.
Survival rate of women and children from upper class was more than the survival rate of men.
Motivation: The motivation for this project was to get first hand experience in analysing any dataset. And how to apply various machine learning algorithms to make predictions.
The dataset is available on Kaggel. Help from Kernels and youtube videos from David Langer (https://www.youtube.com/watch?v=32o0DnuRjfg) has been taken for the successfull completion of this project.