Observed arrival · 2026-09-04
How Models Learn, One Chapter at a Time
An interactive, illustrated explanation of machine learning for readers who want the ideas without starting from equations or model-building.
Field notes
The project organizes machine-learning concepts as a numbered visual sequence rather than a conventional reference manual. Its visible curriculum runs from error measurement and slopes through gradient descent, layered machines, and backpropagation, then extends to embeddings, attention, and encoder-decoder systems. Chapter 4 is marked published while the other listed chapters are presented as forthcoming, and the homepage says each chapter remains available once published. It also explicitly states that there are no accounts, cookies, or analytics.
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