Getting Started with Caffe - Deep Learning Framework Introduction - Class 3

Getting Started with Caffe - Deep Learning Framework Introduction - Class 3

NVIDIA Developer via YouTube Direct link

What does LnDB mean

36 of 45

36 of 45

What does LnDB mean

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Getting Started with Caffe - Deep Learning Framework Introduction - Class 3

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  1. 1 Introduction
  2. 2 Agenda
  3. 3 What is Caffe
  4. 4 What does Caffe do
  5. 5 How does Caffe work
  6. 6 Data preprocessing
  7. 7 Defining a deep neural network
  8. 8 Defining loss functions
  9. 9 Training your network
  10. 10 Output from Caffe
  11. 11 Binary model files
  12. 12 Model Zoo
  13. 13 Localization
  14. 14 Pixel Level Classification
  15. 15 Sequence Learning
  16. 16 Transfer Learning
  17. 17 GPU acceleration
  18. 18 QDNNI
  19. 19 Jetson TK1
  20. 20 Handson lab preview
  21. 21 Getting started with Caffe lab
  22. 22 Questions
  23. 23 Tesla GPUs
  24. 24 Which frameworks are most popular
  25. 25 Can I use Caffe without the GPU
  26. 26 Model file compatibility
  27. 27 QDNN requirements
  28. 28 Multiple GPUs
  29. 29 Depth Images
  30. 30 Giraffes vs Horses
  31. 31 Embedded Deployment
  32. 32 Continuous Learning
  33. 33 Inline Comments
  34. 34 Where can I learn how to format the database
  35. 35 What does LevelDB mean
  36. 36 What does LnDB mean
  37. 37 What does Batch Size mean
  38. 38 How many iterations should I use
  39. 39 Can I use the C API
  40. 40 Endtoend deep learning
  41. 41 Multivariate regression
  42. 42 Defining custom layers
  43. 43 Sensor fusion
  44. 44 Read images from OpenCV
  45. 45 Caffe models

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