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# Digging deeper and deeper into deep learning and artificial neural networks

**[Medium](https://daily.dev/sources/medium_js)** · 19 min read · 6 upvotes · 0 comments

## Summary

This post explores the major architectures of deep neural networks, including RNN, LSTM, and CNN. It also compares the sequential and functional approaches in deep learning and discusses the types of feedforward neural networks. The post emphasizes the importance of choosing the right architecture for building neural networks and provides code examples for implementation.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://ai.gopubby.com/digging-deeper-and-deeper-into-deep-learning-and-artificial-neural-networks-b41570db6259>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#data-science](https://daily.dev/tags/data-science), [#architecture](https://daily.dev/tags/architecture), [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks), [#lstm](https://daily.dev/tags/lstm)

[View this post on daily.dev](https://daily.dev/posts/digging-deeper-and-deeper-into-deep-learning-and-artificial-neural-networks-zb3z6i1if)

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