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# Step-by-step guide to building an artificial neural network and observing how overfitting occurs with MNIST and CNN architecture

**[Medium](https://daily.dev/sources/medium_js)** · 21 min read · 4 upvotes · 0 comments

## Summary

A step-by-step guide to building an artificial neural network with the MNIST dataset using CNN architecture. The post covers accessing the data, data preprocessing, normalization, model architecture design, model compilation, training, evaluation, and detecting overfitting.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://ai.gopubby.com/step-by-step-guide-to-building-an-artificial-neural-network-and-observing-how-overfitting-occurs-84961f96c7e8>

---

Tags: [#deep-learning](https://daily.dev/tags/deep-learning), [#data-processing](https://daily.dev/tags/data-processing), [#overfitting](https://daily.dev/tags/overfitting), [#mnist](https://daily.dev/tags/mnist)

[View this post on daily.dev](https://daily.dev/posts/step-by-step-guide-to-building-an-artificial-neural-network-and-observing-how-overfitting-occurs-wit-qyifzfnen)

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