Machine learning models can be excellent when tested on the data used for training, but quite often they fail to live up to expectations when real-world data are used. The reason for this gap is mostly overfitting: the model ends up learning noise and idiosyncrasies rather than general patterns. Regularization (L1/L2) may be a rather…
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