Why Machine Learning Models Fail… and How to Succeed

Reasons for Failure

Expectations

Solution: Understand the Why

Data

  • Availability of the data required for the problem
  • Data quality
  • Relevance to the problem
  • Data bias

Solution: Educate and Communicate

Model Generalization

Solution: Have a Good Model Training and Validation Process

The “Proof of Concept”

Solution: POCs are Not Bad, but the Execution and Expectations Are

Fitting a Model and Getting the Predictions

Solution: Begin with the End

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As the market leader in intelligent solutions, we help organizations make smarter decisions and act on them. Learn more at atrium.ai

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