Machine learning and trend analysis in PHP
summary
Overview of concrete methods and outcomes: PHP code uses the PHP ML library to train models with a simple four-step flow (data, train, ask, predict), running least squares regression to fit lines (example: 64 → 4.05, 60 predicted 3.3 vs stored 3.1) and k‑nearest neighbors for clustering/classification. Examples include SamKnows broadband fault detection and root‑cause correlation, ecommerce association rules for item placement, automatic blog tagging and NLP for legal discovery. Demos and quick scripts run in a few lines and produce useful though imperfect predictions.
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chapters (7)
- 0:00Introduction to ML
- 2:25The learning process
- 10:45Supervised learning
- 18:24Unsupervised learning
- 27:21ML algorithms in practice
- 37:07PHP implementation
- 40:52Practical use cases
