One of the famous stories is Titanic a luxury steamship that sank into the deep blue ocean in 1912. Leading to the deaths of more than 1,500 passengers and crew. But it seems some groups of people were more likely to survive than others. In this project, we will use a machine learning technique in order to analyze and build a predictive model to find the factors and predict passenger who is to survive or die from this catastrophe. Data description:

• Survival - Survival (0 = No; 1 = Yes). Not included in test.csv file.
• Pclass - Passenger Class (1 = 1st; 2 = 2nd; 3 = 3rd)
• Name - Name
• Sex - Sex
• Age - Age
• Sibsp - Number of Siblings/Spouses Aboard
• Parch - Number of Parents/Children Aboard
• Ticket - Ticket Number
• Fare - Passenger Fare
• Cabin - Cabin
• Embarked - Port of Embarkation (C = Cherbourg; Q = Queenstown; S = Southampton)