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Can anybody suggest a good tutorial or book for neural networks in Lisp, or a blog, or share some code sample?
I have experience with neural netowrks in the imperative languages C++, Java, C#, but I want to try it in Lisp.
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Lisp's ability to compute with symbolic expressions rather than numbers makes it convenient for artificial intelligence (AI) applications. While it isn't as popular as C, Python or Perl, Lisp is still used for AI programming as well as several other functions.
Multilayer Perceptron. Convolutional Neural Network. Radial Basis Functional Neural Network. Recurrent Neural Network.
The very most disadvantage of a neural network is its black box nature. Because it has the ability to approximate any function, study its structure but don't give any insights on the structure of the function being approximated.
Convolutional neural networks (CNNs) have an advantage over RNNs (and LSTMs) as they are easy to parallelise. CNNs are widely used in NLP because they are easy to train and work well with shorter texts.
The seminal book AI: a modern approach includes LISP source code on the website: link Specifically, check out the Learning chapter (perceptron etc)
In the same vein you have Paradigms of AI in Lisp, but it doesn't really touch neural networks if I remember correctly.
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While the question is old and my answer is late, I still think it's valuable.
Recently I was looking for some resources on Machine Learning in Common Lisp(hence why I found this question). After doing some more research, I've found this codebase. It contains many interesting things, such as Boltzmann Machines, feed-forward and recurrent backprop neural networks. The author also has other libraries, such as evolutionary algorithms. This code is sure a good way to start.
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