Machine learning developers often encounter models that perform well on a data set, but dont live up to expectations when used on unseen or test data. This problem is called Overfitting. If you would like to learn more about Overfitting and how to avoid it, read on.
Very nice explanation of a very common problem. Examples are given in such a way that any one can understand easily. Also remedies for under fitting and over fitting are given in a structured manner.keep it up.
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Mayank Tripathi
16 Jun 2020 02:10:44 AM