Setting Up Machine Learning Projects - Full Stack Deep Learning - March 2019

Setting Up Machine Learning Projects - Full Stack Deep Learning - March 2019

The Full Stack via YouTube Direct link

How to create good human baselines Quality of baseline Low

19 of 21

19 of 21

How to create good human baselines Quality of baseline Low

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Setting Up Machine Learning Projects - Full Stack Deep Learning - March 2019

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  1. 1 Intro
  2. 2 Goals for the lecture
  3. 3 Running case study - pose estimation
  4. 4 Hypothetical Co. Full Stack Robotics (FSR) wants to use pose estimation to enable grasping
  5. 5 Lifecycle of a ML project
  6. 6 Outline of the rest of the lecture
  7. 7 Key points for prioritizing projects
  8. 8 A (general) framework for prioritizing projects
  9. 9 Why are accuracy requirements so important?
  10. 10 Product design can reduce need for accuracy
  11. 11 Another heuristic for assessing feasibility
  12. 12 Key points for choosing a metric
  13. 13 Review of accuracy, precision, and recall
  14. 14 Why choose a single metric?
  15. 15 How to combine metrics
  16. 16 Combining precision and recall
  17. 17 Thresholding metrics
  18. 18 Example: choosing a metric for pose estimation
  19. 19 How to create good human baselines Quality of baseline Low
  20. 20 Key points for choosing baselines
  21. 21 Questions?

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