What do you mean by Regularisation? What are L1 and L2 Regularisation?

Data Science, AI and ML
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Regulation is a method to improve your model which is Overfitted by introducing extra terms in the loss function. This helps in making the model performance better for unseen data.

There are two types of Regularisation :

L1 Regularisation – In L1 we add lambda times the absolute weight terms to the loss function. In this the feature weights are penalised on the basis of absolute value.

L2 Regularisation – In L2 we add lambda times the squared weight terms to the loss function. In this the feature weights are penalised on the basis of squared values.