I am currently learning about Ridge and Lasso Regression, which leads me to learn about L1 and L2 regularization. There's a phrase saying
L2 Regularization doesn't result in sparse model and
L1 regularization can result in sparse models with few coefficients.
I know what sparse matrix means, a matrix with very few non-zero elements (hope I am not wrong about it) but I am not able to understand what a
sparse model means. I tried to search about it on google but didn't find any satisfying answer. I am seeing this term a lot now, so It will be great if you can help me understand this.
I am not a math guy and so please be soft and use less terminology while answering.