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Machine Learning Basic Concepts

Selected Course Topics

Best Viewed at 1040p

MLP

What is a Typical Machine Learning Process

  • Establish prediction objectives

  • Create learning & test data

  • Learn model and measure performance

  • Make predictions, support use cases, perform simulations & influence analysis

SHA

Model Explainability 

  • Basic Example Demonstrating Shapley 

  • Method Deconstructs any Output Result Set

  • Results are Explainable, Human Readable and Actionable

MT

Machine Learning Types

  • Supervised & Unsupervised

  • Introduction to Classification & Regression

  • When to Use Each

ME

What is a Machine Learning Method

  • Classification & regression

  • 100's of methods to choose

  • Selection criteria - performance, cost, explainability, preference

CV

Cross Validation

  • Cross-validation

  • Testing

  • Learning Curves

CP

How to Measure Classification Performance

  • Metrics

  • Confusion matrix

  • Learning curve

RP

How to Measure Regression Performance

  • Metrics

  • Unity plot

  • Learning curve

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