Table of Contents

• 1.Background
• 2.Introduction
• 3.Brief Introduction to the used libraries
• 4.Understanding the data
• 5.Importing the necessary libraries
• 6.Loading the dataset
• 7.Meet and Greet the data
• 8.Pandas Profiling to get the overview of data
• 9.Handling the missing values
• 10.Data Visualization
  • 10.1 Visualizing the outcome column
  • 10.2 Plots to analyze the data
  • 10.3 Visualizing the Outliers
  • 10.4 Pairplot, Correlation matrix and HeatMap
  • 10.5 Analysis of each parameter w.r.t outcome parameter
  • 10.6 Analysis of each parameter with each respect to each other
• 11.Baseline Model
• 12.Feature Engineering
  • 12.1 Handling Outliers
  • 12.2 Features Scaling
• 13.Conclusion