R Project Template with the Iris Dataset

Working through machine learning problems from end-to-end requires a structured modeling approach. Working problems through a project template can encourage you to think about the problem more critically, to challenge your assumptions, and to get good at all parts of a modeling project.

Any predictive modeling machine learning project can be broken down into about six common tasks:

  1. Define Problem
  2. Summarize Data
  3. Prepare Data
  4. Evaluate Algorithms
  5. Improve Accuracy or Results
  6. Finalize Model and Present Results

The HTML formatted report can be found here on the website.