AI for PHP Developers (examples)
AI for PHP
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Introduction
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Getting Started
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ML Ecosystem in PHP
Part I. The Mathematical Language of AI
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What is a model
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Vectors, dimensions and feature spaces
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Distances and similarity
Part II. Learning as Optimization
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Error, loss functions, and why they are needed
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Linear regression as a basic model
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Gradient descent on fingers
Part III. Classification and probabilities
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Probability as degree of confidence
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Logistic regression
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Why Naive Bayes works
Part IV. Proximity and data structure
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The k-nearest neighbors algorithm and local solutions
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Decision Trees and space partitioning
Part V. Text as mathematics
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Why do words turn into numbers
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Bag of Words and TF–IDF
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Embeddings as continuous spaces of meaning
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Transformers and context: from static vectors to understanding meaning
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Tokens, context windows, and chunking: how LLM sees text
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Named Entity Recognition (NER) - extracting entities from text
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Hands-on: embeddings in PHP with transformers
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RAG: Retrieval-Augmented Generation as an engineering system
Part VI. Neural Networks and Data Mining
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Perceptron and fully connected network
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Backpropagation – why it works
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Convolutional neural networks (CNN)
Home
Part VI. Neural Networks and Data Mining
Convolutional neural networks (CNN)
Convolutional neural networks (CNN)
A minimal PHP example (intuitive)