First of all Regularization and Normalization are two different terms. Regularization is used to prevent overfitting by either knocking out few parameters to zero(L1) or bringing some parameters very close to being zero(L2). Normalization is used to bring the data to desired centered mean( Gaussian Distribution). Normalization basically bounds the data to be in a specific distribution rather than having outliers and other stuff which in turns helps your model to learn the parameters efficiently.