What is regularization? What are some of its techniques?

Regularization is used to reduce over-fitting in machine learning models. It helps the models to generalize well and make them robust to outliers and noise in the data.

Regularization Techniques

There are mainly two types of regularization,

1. L1 Regularization (Lasso regularization) - Adds the sum of absolute values of the coefficients to the cost function.
2. L2 Regularization (Ridge regularization) - Adds the sum of squares of coefficients to the cost function.

• Where determines the amount of regularization.

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