Machine Learning

This section will provide extra instructional information useful to your success.

The primary takeaways are:

1. Graph the results of your Machine Learning Model
2. Strive to understand HOW your model is making its predictions
3. Work to get a ‘Goldilocks’ fit model (not underfitted, not overfitted)
4. Explore the Fairness of your model

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Table of contents

• Feature Importance
• Assessing Accuracy
• Classification
• Regression - Distance Study
• Classification - Fully Random
• When to Avoid Using Machine Learning