Machine Learning: deciphering the hype

Ddd6d3bac7772fa67fc5e312a18bdaec?s=47 sammyd
September 05, 2017

Machine Learning: deciphering the hype

With the advent of Core ML in iOS 11, machine learning is making its mainstream debut. Let's discover what machine learning actually is, what you can do with it, how it works and see how Core ML fits in.

Ddd6d3bac7772fa67fc5e312a18bdaec?s=128

sammyd

September 05, 2017
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  1. Machine Learning deciphering the hype

  2. Core ML

  3. With Core ML, you can integrate trained machine learning models

    into your app. — devloper.apple.com
  4. None
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  6. classification tell me which of these groups the input falls

    into
  7. regression estimate an output value given this input

  8. clustering how many different classes does the data fall into?

  9. 1 collect data

  10. 2 ground truth

  11. 3 feature vectors

  12. 4 train model

  13. 5 test model

  14. 6 repeat 3, 4 & 5

  15. 7 deploy model

  16. 8 perform prediction

  17. Machine Learning 1. Collect data 2. Ground truth 3. Feature

    vectors 4. Train model 5. Test model 6. Repeat 3, 4 & 5 7. Deploy model 8. Perform prediction
  18. Machine Learning 1. Collect data 2. Ground truth 3. Feature

    vectors 4. Train model 5. Test model 6. Repeat 3, 4 & 5 7. Deploy model 8. Perform prediction
  19. Linear Regression Support Vector Machine Tree Ensembles Bayesian Networks Neural

    Networks
  20. Core ML provides an abstraction across different model types

  21. model interchange format

  22. device optimised implementation

  23. consistent API

  24. that just leaves the hard part

  25. SVM support vector machine

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  28. example: sentiment analysis

  29. bag of words

  30. demo

  31. convolutional neural networks

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  45. example: salient object subitizing

  46. demo

  47. conclusion

  48. Core ML is a small part of the story

  49. useful nonetheless

  50. format optimisation API

  51. potentially exciting times

  52. github.com/sammyd /iOSDevUK17_CoreML - @iwantmyrealname