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Loss and gradients without the formulas: backprop is a graph walk

This story is from 2026-10-22. It is preserved in the archive; the latest stories are on the live feed.

Originally published at cchinchilla.dev . Part 8 of From code to weights, a 12-part series on ML fundamentals for engineers. Part 7 ended on four changes to a block, each one baked into the weights. Every one of those weights was learned. This part reads how: a single number that says how wrong the…

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  1. 2026-10-22 13:00 · DEV Community — Machine Learning
    Loss and gradients without the formulas: backprop is a graph walk

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