Data Science, Machine Learning, Regression, Data Analysis, Statistics.
from fitting the training data too closely. Regularization in regression models, like Lasso and Ridge, involves adding a penalty term to the loss function to constrain the model coefficients. This helps prevent overfitting by penalizing large coefficients, leading to simpler models. Let’s