The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships.
One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class.
In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy.
Excel would have been my first weapon of choice, but I wanted to try a new approach and a new analytical tool.
I’ve a use for R in my salaried role, and can see how I can utilise what I’ve learned in the guide in real World projects.
So thanks to Trev I now have a top 400 ranked score, and I am driven to do better. Think I’ll manipulate the data in Excel, rather than mastering regex in R, let’s see how high up the rankings I can get 🙂