Predicting the Likelihood of Survival of Titanic’s Passengers by Machine Learning

Abstract

The sinking of RMS Titanic is presumably one of the most infamous and disastrous shipwrecks in history. During her maiden voyage and early morning hours of April 15, 1912, the Titanic regrettably sank after colliding with an iceberg, killing an approximate of 1502 passengers and crew out of 2224 making it one of many of the deadliest commercial maritime in history till date. The entire international community was deeply shocked and saddened after hearing the news of this sensational disaster which resulted in improved ship safety legislation. Her architect, Thomas Andrews died in the disaster. An eye-opening observation that came forth from the sinking of Titanic is the fact that some individuals had a better chance at surviving than the others. Kids and women had been given foremost priority. Social classes were heavily stratified in the early twentieth century, this was especially implemented on the Titanic Firstly, the aim is use and apply exploratory data analytics (EDA) to uncover previously unknown or hidden facts in the data set available. Then the task is to later anoint various machine learning models to conclude the study of which types of individuals are more likely to live. The outcomes of application of the different machine learning models were then set side by side and analyzed based upon precision.