In this blog, we will write about regularization. we will discuss its purpose and how it works.

If there is one thing that jeopardizes a perfect Neural Network that would be overfitting. Overfitting refers to situations where the model has fit the training data so well that the model captures the noise and random fluctuations.

I assume we already know about using a validation set and early stopping in order to prevent overfitting from happening. Unfortunately, I have to say that these approaches are not 100% reliable. There may be certain situations where the validation loss stays the same or…

Ali Mahzoon

M.Sc in Information Technology

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