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Tensorflow for Android Developers

Joe Birch
March 26, 2018
Technology
3
230

Tensorflow for Android Developers

Joe Birch

March 26, 2018
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Transcript

  1. TENSORFLOW
    FOR ANDROID DEVELOPERS
    JOE BIRCH - @HITHEREJOE - ANDROID LEAD @BUFFER - GDE @ANDROID

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  2. MACHINE LEARNING 101
    Get data
    Clean, prep &
    manipulate data
    Train Model
    Test data
    Improve

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  3. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

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  4. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

    View Slide

  5. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

    View Slide

  6. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

    View Slide

  7. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

    View Slide

  8. MACHINE LEARNING 101
    Unsupervised
    Learning
    Supervised
    Learning
    Clustering
    Classification
    Regression

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  9. MACHINE LEARNING AND MOBILE

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  10. MACHINE LEARNING AND MOBILE

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  11. TENSORFLOW

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  12. TENSORFLOW

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  13. COMPUTATION GRAPHS
    C
    D F
    A
    B E

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  14. NEURAL NETWORKS
    Some Image Result

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  15. NEURAL NETWORKS
    Some Image Result

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  16. NEURAL NETWORKS
    Some Image Result

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  17. NEURAL NETWORKS
    Some Image Result
    Pre-trained model

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  18. BUILDING OUR OWN IMAGE
    CLASSIFIER USING A MOBILE NET

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  19. TENSORBOARD

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  20. TENSORBOARD

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  21. TENSORBOARD
    tensorboard --logdir tf_files/training_summaries &

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  22. TRAINING DATA

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  23. RETRAINING THE MODEL

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  24. RETRAINING THE MODEL

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  25. RETRAINING THE MODEL

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  26. RETRAINING THE MODEL

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  27. RETRAINING THE MODEL

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  28. RETRAINING THE MODEL

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  29. RETRAINING THE MODEL

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  30. RETRAINING THE MODEL

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  31. RETRAINING THE MODEL

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  32. RETRAINING THE MODEL

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  33. RETRAINING THE MODEL

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  34. HOW TRAINING WORKS?

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  35. HOW TRAINING WORKS?

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  36. HOW TRAINING WORKS?

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  37. HOW TRAINING WORKS?

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  38. HOW TRAINING WORKS?

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  39. HOW TRAINING WORKS?

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  40. MODEL ACCURACY

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  41. MODEL ACCURACY

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  42. OPTIMISING THE MODEL
    Model
    Operation
    Model
    Operation
    Model
    Operation
    Model
    Operation
    Load graph
    Don’t load
    graph
    Operation
    supported?

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  43. OPTIMISING THE MODEL

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  44. OPTIMISING THE MODEL

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  45. OPTIMISING THE MODEL

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  46. OPTIMISING THE MODEL

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  47. OPTIMISING THE MODEL

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  48. QUANTISATION

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  49. QUANTISATION

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  50. QUANTISATION

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  51. QUANTISATION

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  52. OPTIMISING THE MODEL

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  53. ADDING THIS TO AN APP
    Add Dependancy
    Create TF
    Reference
    Feed data Run inference
    Fetch result
    Handle
    confidence

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  54. ADDING THIS TO AN APP

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  55. ADDING THIS TO AN APP
    // convert to 3d array (width / height / color)

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  56. ADDING THIS TO AN APP

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  57. ADDING THIS TO AN APP

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  58. ADDING THIS TO AN APP
    Shape of our input

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  59. ADDING THIS TO AN APP

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  60. ADDING THIS TO AN APP

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  61. ADDING THIS TO AN APP

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  62. ADDING THIS TO AN APP
    https://github.com/tensorflow/tensorflow

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  63. CONCLUSION

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