Probabilistic Deep Learning in TensorFlow - The Why and How - ODSC Europe 2019

Probabilistic Deep Learning in TensorFlow - The Why and How - ODSC Europe 2019

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Negative log likelihood

25 of 25

25 of 25

Negative log likelihood

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Probabilistic Deep Learning in TensorFlow - The Why and How - ODSC Europe 2019

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  1. 1 Intro
  2. 2 Overview
  3. 3 TensorFlow dependencies
  4. 4 Building a regression model
  5. 5 Exploring the data
  6. 6 Creating a chaos model
  7. 7 Defining a helper class
  8. 8 Results
  9. 9 Early stopping
  10. 10 Plotting predictions
  11. 11 Takeaways
  12. 12 Replacing Dense Layer
  13. 13 Dense Variational
  14. 14 Prior Distribution
  15. 15 Example Batch
  16. 16 The Trick
  17. 17 Inspecting Layers
  18. 18 Model Results
  19. 19 Model Predictions
  20. 20 Input Predictions
  21. 21 Call Banks
  22. 22 Plot History
  23. 23 Summary
  24. 24 Regression with probabilistic layers
  25. 25 Negative log likelihood

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