The titanic was one of the greatest engineering marvels of its time. Few could have forseen the disastrous end the ship would meet including the deaths of more than 1500 individuals. However, were these deaths arbitrary, or was their a pattern to the madness that ensued. It is well known that "save the women and children" was a major objective that increased survival rates of those groups. However, to what extent does such a pattern appear in the data, and what other trends can we discover?
In this repository, the titanic classification notebook includes some exploratory data analysis as well as a random forest classifier to predict the survival of a passenger given information about them. This model is then saved using joblib for use later on. The interactive_demo notebook uses this model in conjuction with a Dash app. This Dash app allows for a user to manipulate the charateristics of a traveler (the inputs for the classifier) and see the prediction of suvival.
