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First Steps to Interpretable Machine Learning

First Steps to Interpretable Machine Learning

MLCon | Machine Learning Conference via YouTube Direct link

Feature Value

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Feature Value

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Classroom Contents

First Steps to Interpretable Machine Learning

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  1. 1 Introduction
  2. 2 About Leverage Solutions
  3. 3 Agenda
  4. 4 Motivation
  5. 5 Project Inspiration
  6. 6 Automated Check
  7. 7 Kickstarter
  8. 8 Data
  9. 9 Cat Boost
  10. 10 Beckers Column
  11. 11 Second Model
  12. 12 Calculation Example
  13. 13 Average Contribution
  14. 14 Feature Value
  15. 15 Conclusion

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