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I've used https://github.com/paulrzcz/HSvm (libsvm) for some things – if all you need is svm-like classification and your data is of the easily predictable kind (so you don't have to experiment much with different models), that might be enough (just m <- SVM.train (SVM.NuSvc 0.25) (SVM.RBF 1) trainFeats; prediction <- SVM.predict m inputFeats, remember to scale numbers to 0..1).
Alternatively something like https://github.com/dpkatz/HaskellGBM – you can train a model in whatever language you want (or just on the command-line) and then easily use it from Haskell.
IF (big if) it turns out you do need deep learning then doing it in Hasktorch http://hasktorch.org/ could be a fun learning project. The team making it is super nice and responsive, too
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