Smart ML Experiment Tracking and Model Registry with Neptune.AI Platform

Smart ML Experiment Tracking and Model Registry with Neptune.AI Platform

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Smart ML Experiment Tracking and Model Registry with Neptune.AI Platform

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  1. 1 - Video Start
  2. 2 - Introduction
  3. 3 - Why and Why?
  4. 4 - 3 Key Features
  5. 5 - Platform Service Status
  6. 6 - MLOps Tutorials
  7. 7 - Get Platform Access
  8. 8 - Jupyter Notebook colab & GitHub
  9. 9 - Heart Disease Detection ML Experiment
  10. 10 - ML Experiment in Keras/TensorFlow
  11. 11 - Export colab notebook to GitHub
  12. 12 - Adding Neptune Tracking code
  13. 13 - Create Tracking Project
  14. 14 - Initialize Neptune runtime objects
  15. 15 - ML Experiment with Neptune Objects
  16. 16 - Neptune Callback with ML Experiment
  17. 17 - Neptune ML Tracking Dashboard
  18. 18 - Adding another Experiment
  19. 19 - Comparing Experiments
  20. 20 - Custom content image Tracking
  21. 21 - More Experiments tracking
  22. 22 - Adding Jupyter notebook as resource
  23. 23 - Pushing Colab notebook to GitHub
  24. 24 - Recap
  25. 25 - Credits

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