Dear community, I'm trying to understand what specifically are the classification and regression algorithms in BME AI Studio for my specific use case I see in the BME AI studio manual that these are based on "Neural Nets," and I see that the software offers plentiful data regarding these algorithms' performance. And that is uses an ADAM optimization algorithm to train these neural networks But I have very little details on the neural networks themselves and I don't see in the manuals/specs what types of neural networks are used. Since this is classification, I'm guessing this might be a Multi-Layer Perceptron or a Convolutional Neural Network. I was wondering if you could please offer some context, and maybe point me to any documentation on these algorithms specifically. I'd like to know what these algorithms assume of the data, what their fallbacks are, etc., so I can plan for my use case and decide whether designing something custom would be more appropriate @BSTRobin your support would be much appreciated here --pardon the direct call out, I saw that you were responsing to many requests Thank you for your time and attention--wishing you the best
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