Owaiskhan9654/Dropout-in-Neural-Networks

Deep NNs with large number of parameters are powerful machine learning systems. But overfitting is a serious problem in these networks. These NNs are slow to use, making difficulties to deal with overfitting by combining the predictions of different large NNs at testing time. Dropout could be a technique to manage these problems.

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