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Java Deep Learning Projects by Md. Rezaul Karim

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Unsupervised learning

In unsupervised learning, an input set is supplied to the system during the training phase. In contrast with supervised learning, the input objects are not labeled with their class. For classification, we assumed that we are given a training dataset of correctly labeled data. Unfortunately, we do not always have that advantage when we collect data in the real world.

For example, let's say you have a large collection of totally legal, not pirated, MP3 files in a crowded and massive folder on your hard drive. In such a case, how could we possibly group songs together if we do not have direct access to their metadata? One possible approach could be to mix various ML techniques, but clustering is often the best solution. ...

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