The L1 norm adds a penalty proportional to the absolute values of the coefficients, leading to sparse solutions

The L1 norm encourages all coefficients to be close to zero but not exactly zero.

The L1 norm is less effective than the L2 norm for high-dimensional data.

The L1 norm is the sum of the squared values of the coefficients