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# AI Fundamentals: What is a Neuron?

**[Medium](https://daily.dev/sources/medium_js)** · 9 min read · 1 upvotes · 0 comments

## Summary

A beginner-friendly breakdown of how artificial neurons work, covering the four core components: inputs, weights, bias, and activation functions. Explains the math behind the weighted sum formula, why non-linearity matters, and how common activation functions (Sigmoid, Tanh, ReLU) differ. Includes a practical Python implementation of a single neuron using sigmoid activation, and connects the concept to how language models generate text using embeddings, logits, and softmax.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pub.towardsai.net/ai-fundamentals-what-is-a-neuron-62e76a6f3500>

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Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#python](https://daily.dev/tags/python), [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks)

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