Python Machine Learning Workflow

This example illustrates fitting and comparing several Machine Learning algorithms for classifying the binary label 'left' in the Human Resource data set.
The steps include:
PREPARE AND EXPLORE
  a) Data is loaded into CAS
  b) Explore data, distributions, correlations, and visualizations
PERFORM SUPERVISED LEARNING
  a) Fit a model using Logistic Regression
  b) Fit a model using Gradient Boosting
  c) Hands-on Problem - Fit a model using Random Forest
EVALUATE AND IMPLEMENT
  a) Score the data
  b) Assess model performance
  c) Generate ROC and Lift charts
  d) Hands-on Problem - Score, Assess, ROC charts for Random Forest model and Compare with Logistic and Gradient Boosting