Titanic Dataset survival Prediction
|Provided by||Arun Kaashyap Arunachalam – MS in Computer Science|
Hey guys since the focus of this club is to help introduce members to data science and help learn machine learning this is a very good project to start with. In this project we discuss classification which is a very basic task in the field of data science and machine learning.
Don’t worry if you struggle with this easy project everybody starts somewhere.
Don’t be afraid to ask members of the team for any help.
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.
This project is from Kaggle and the dataset can be accessed at here with information regarding the dataset and the features available for training the classification model.