Why scaling matters in in lasso regression?



While learning about lasso regression I found that to use lasso regression we have to standardize the predictors but when we have to use normal methods like the linear regression in which the methods use the residual sum of squares method to find the best fit we do not need to standardize the predictors. I want to know the reason behind this.


Could you also please share the link for the standardization in lasso regression? It will be really helpful. Thank you.