Observed arrival · 2026-09-14
NeuralMath: The Math Inside a Neural Network
A multilingual, code-first lesson that follows a complete NumPy neural network from synthetic data to its learned decision boundary.
Field notes
The lesson uses mass and diameter to classify synthetic apples and oranges, then standardizes those inputs before training a two-input, twelve-neuron, one-output network. Its 49 trainable parameters are intentionally small enough to inspect, and the page writes the chain rule directly rather than relying on automatic differentiation. The material links to Python source, a GitHub repository, Google Colab, and a Portuguese companion manuscript, with the same project presented across six languages.
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