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In this study, we analyzed the hyper-parameters
which are frequently used in deep learning methods on a generated
DNN. On the Fashion-MNIST dataset, we had chance to interpret
the evolution of the model to the end as a result of tests performed
on a low epoch number. At the end of the study, we reached a
success rate of about 90 percent on the test data and showed that
the selected hyper-parameters by created model were the most
accurate.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Yusuf Yargı Baydilli
Ü. ATİLA