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.

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