The sinking of the RMS Titanic is one of the most notorious 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 harrowing tragedy shocked the international community and led to better safety regulations for ships. In this problem, we're asked to complete the analysis of what sorts of passengers were likely to survive the tragedy using machine learning. So its our job to predict if a passenger survived from the sinking Titanic or not with the help of machine learning. So its a binary classification problem hosted by kaggle.

Train and test data are provided in this repository. The data has been split into two groups. Training set (train.csv) and test set (test.csv).

The training set should be used to build your machine learning models. For the training set, we provide the outcome (also known as the “ground truth”) for each passenger. Our model will be based on “features” like passengers’ gender and class. We will also use feature engineering to create new features.

The test set should be used to see how well our model performs on unseen data. For the test set, the ground truth for each passenger is not provided. It is our job to predict these outcomes. For each passenger in the test set, use the model you trained to predict whether or not they survived the sinking of the Titanic.