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I know 'easy to use' is going to be subjective, so let me qualify the question a little. Is there a library or working scrap of code that I can essentially copy into my project, change the number of neurons in each layer, the number of layers, and the source of the inputs and then click run. I've written at least 15 of these myself, not a single one has worked properly - I need to see something working in a language I understand so I can get to grips with why I'm apparently a moron!

(I can post some of my own code if anyone is interested, but it's lengthy and not too related to the question)

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I have no personal experience with it, but I came across Accord, which has limited support for neural networks. Honestly, .net does not have a machine learning community, so you might be better off using something else if you do not want to DIY.

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Take a look at the C# ENCOG framework:

http://www.heatonresearch.com/encog/

https://github.com/encog

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  • $\begingroup$ This does not provide an answer to the question. To critique or request clarification from an author, leave a comment below their post. - From Review $\endgroup$
    – Dawny33
    Commented May 28, 2016 at 3:04
  • $\begingroup$ If he take a look at the encog github, he will find some simple examples using neural networks in C# that he can copy and paste. Sorry if this does not help. github.com/encog $\endgroup$
    – Icaro Bombonato
    Commented May 30, 2016 at 12:14
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Try Seq2SeqSharp. Seq2SeqSharp is a tensor based fast & flexible encoder-decoder deep neural network framework written by .NET (C#). It can be used for sequence-to-sequence task, sequence-labeling task and sequence-classification task and other NLP tasks. Seq2SeqSharp supports both CPUs and GPUs. It's powered by .NET core, so Seq2SeqSharp can run on both Windows and Linux without any modification and recompilation.

It's built-in Transformer encoder/decoder, LSTM and many kinds of layers and also provide many machine translation system as demo.

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