• Introduction
  • Explore Data and Identify Missing Values
Dealing with Missing Values
  • Treat Embarked Variable
  • Treat Age Variable
  • Treat Cabin and Recode Sex Variable
Feature Engineering : Numerical Features
  • Create Family Size and Is Alone Feature from Sibsp and Parch
Feature Engineering : Categorical Features
  • Extract Title from Name Variable
  • Extract Feature from Ticket Variable
Prepare data for Modelling
  • Create Dummy Variables
  • Create Train and Test Datasets
Build Base Model using Python (Logistic Regression)
  • Build Logistic Regression
  • Evaluate Model and Submit to Kaggle