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Using machine learning to improve our WordPress application

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Machine Learning is one of the most trendy things in IT world right now, a bunch of new services pop-up every single moment, large companies have started to implement different features that utilise Machine Learning(ML). But…. how mortal developers and small and medium business can effectively use machine learn to improve their solutions?

In this talk, we are going to discuss the basic concepts around ML and using high-level libraries in JavaScript to implement on ourWordPress Application, described as a friendly Machine Learning library ml5.js will be our entry door to the Machine Learning world.

To wrap up the introduction journey, we will see how we can use ml5.js in a real project. As I mentioned before ml5.js is a Javascript library – the talk is focused on a front-end stack but is open for people who want to learn more about the basic concepts behind machine learning.

Let’s get coding!!!

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Using machine learning to improve our WordPress application

  1. 1. @fellyph Using machine learning to improve our WordPress Application Fellyph Cintra
  2. 2. @fellyph Or: Machine learning for mortal developers
  3. 3. @fellyph @fellyph Deloitte Digital Google Developer Expert
  4. 4. @fellyph Artificial Intelligence ?
  5. 5. @fellyph Artificial Intelligence ???
  6. 6. @fellyph –Arthur Samuel “Field of study that gives computers the ability to learn without being explicitly programmed.”
  7. 7. @fellyph 250 300 100 270 4 151 Example: Normal computation If (x > 200) { side = right; } esle { side = left; } Right - 250 Right - 300 Left - 100 Right - 270 Left - 4 Left - 151
  8. 8. @fellyph Example: AI computation Right - 250 Right - 300 Left - 100 Right - 270 Left - 4 Left - 151 Predict next results
  9. 9. @fellyph Example: AI computation Right - 250 Right - 300 Left - 100 Right - 270 Left - 4 Left - 151 Predict next results
  10. 10. @fellyph AI Terms Natural Language Neural network Datasets Supervised Learning Unsupervised Learning Pre-trained models Machine Learning Deep Learning
  11. 11. @fellyph AI Terms Natural Language Neural network Datasets Supervised Learning Unsupervised Learning Pre-trained models Machine Learning Deep Learning
  12. 12. @fellyph Artificial Intelligence Machine Learning Deep Learning Natural Language Neural Network Supervised  Learning Unsupervised  Learning
  13. 13. @fellyph
  14. 14. @fellyph ML5.js
  15. 15. @fellyph What we can Classify? Images Sounds Text
  16. 16. @fellyph Can we use ML5.js and WordPress?
  17. 17. @fellyph Ναί!!!
  18. 18. @fellyph Steps 1. Create a Gutenberg Block(optional) 2. Define labels(output) - Product ID 3. Training model 4. Export Pre-trained model 5. Apply script to a Gutenberg block
  19. 19. @fellyph LET’S CODE!
  20. 20. @fellyph MAIN FUNCTIONS
  21. 21. @fellyph Training https://youtu.be/ItVJkMss070
  22. 22. @fellyph Initial Setup
  23. 23. @fellyph gotResults function
  24. 24. @fellyph Solution https://youtu.be/I5paRtH7aTw
  25. 25. @fellyph Considerations • KNN model - 500kb • FeatureExtractor model - 5MB(more than 2 labels).
  26. 26. @fellyph Coming soon https://wicg.github.io/shape-detection-api/
  27. 27. @fellyph Chrome support(behind flag) https://developers.google.com/web/updates/2019/01/shape-detection
  28. 28. @fellyph Links https://p5js.org/ https://ml5js.org/ https://github.com/fellyph/ml5js-gutenberg https://www.youtube.com/watch?v=jmznx0Q1fP0 ml5.js course
  29. 29. @fellyph Obrigado (thanks)

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