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