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I'm a complete newbie to NNs, and I need your advice.

I have a set of images of symbols, and my goal is to categorize and divide them into groups of symbols that look alike. Without teaching NN anything about the data.

What is the best way to do this? What type of NN suits the best? Maybe there are any ready solutions?

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This is called "clustering" , If the network is already trained with data that has similar features as of the "symbols", you can use that network with its last classification layer removed , then run a clustering algorithm like "k-means" on top of the vectors obtained from the last layer of the network.

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