Apache Spark Machine Learning Blueprints

ML workflow examples

To further understand machine learning workflows, let us review some examples here.

In the later chapters of this book, we will work on risk modelling, fraud detection, customer view, churn prediction, and recommendation. For many of these types of projects, the goal is often to identify causes of certain problems, or to build a causal model. Below is one example of a workflow to develop a causal model.

1. Check data structure to ensure a good understanding of the data:
   • Is the data a cross sectional data? Is implicit timing incorporated?
   • Are categorical variables used?
2. Check missing values:
   • Don't know or forget as an answer may be recoded as neutral or treated as a special category
   • Some variables may have a lot of missing values
   • To ...