Using machine learning to improve our WordPress application
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. @fellyph Using machine learning to improve our WordPress Application Fellyph Cintra
- 2. @fellyph Or: Machine learning for mortal developers
- 6. @fellyph –Arthur Samuel “Field of study that gives computers the ability to learn without being explicitly programmed.”
- 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. @fellyph Example: AI computation Right - 250 Right - 300 Left - 100 Right - 270 Left - 4 Left - 151 Predict next results
- 9. @fellyph Example: AI computation Right - 250 Right - 300 Left - 100 Right - 270 Left - 4 Left - 151 Predict next results
- 10. @fellyph AI Terms Natural Language Neural network Datasets Supervised Learning Unsupervised Learning Pre-trained models Machine Learning Deep Learning
- 11. @fellyph AI Terms Natural Language Neural network Datasets Supervised Learning Unsupervised Learning Pre-trained models Machine Learning Deep Learning
- 12. @fellyph Artificial Intelligence Machine Learning Deep Learning Natural Language Neural Network Supervised Learning Unsupervised Learning
- 13. @fellyph
- 15. @fellyph ML5.js
- 16. @fellyph What we can Classify? Images Sounds Text
- 17. @fellyph Can we use ML5.js and WordPress?
- 18. @fellyph Ναί!!!
- 19. @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
- 26. @fellyph Considerations • KNN model - 500kb • FeatureExtractor model - 5MB(more than 2 labels).