Core ML: A whistlestop tour

Core ML is a framework that makes is super-easy to query machine learning models on Apple devices. But what is machine learning? Let's find out through the art of badly drawn diagrams.

These slides accompany the talk presented at iOSCon 2018 in London.

Transcript

1. Core ML: a whistlestop tour
2. Core ML
3. With Core ML, you can integrate trained machine learning models into your app. — developer.apple.com
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
39. example: sentiment analysis
40. bag of words
41. demo
42. convolutional neural networks
56. example: salient object subitizing
57. demo
58. conclusion
59. Core ML is a small part of the story
60. useful nonetheless
61. format optimisation API
62. potentially exciting times
63. github.com/sammyd /iOSCon2018_WhistlestopCoreML - @iwantmyrealname