# Training Neural Networks with Backpropagation. Original Publication.

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Neural networks have been a very important area of scientific study that has evolved by different disciplines such as mathematics, biology, psychology, computer science, etc.**Data R Value**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The study of neural networks leapt from theory to practice with the emergence of computers.

Training a neural network by adjusting the weights of the connections is computationally very expensive so its application to practical problems took until the mid-80s when a more efficient algorithm was discovered.

That algorithm is now known as back-propagation errors or simply backpropagation.

One of the most cited articles on this algorithm is:

**Learning representations by back-propagating errors**

*Nature*

**323**, 533 – 536 (09 October 1986)

Although it is a very technical article, anyone who wants to study and understand neural networks is obliged to pass through this material.

I share the entire article in:

https://github.com/pakinja/Data-R-Value

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