The Titanic Project is one of Kaggle's data science basic projects, and I have been able to use Python and its libraries to design a classification model to determine the survival of Titanic passengers.

I just used the train file and split the dataset into two parts for learning and predicting. You go according to what kaggle wants.

The sinking of the Titanic is one of the most infamous shipwrecks in history.

On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew.

While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others.

In this challenge, we ask you to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).

Titanic - Machine Learning from Disaster