Answer Posted / Seema Pal

Regularization is a technique used to prevent overfitting in machine learning models by adding a penalty term to the loss function during training. Regularization methods encourage simpler models that generalize better to unseen data. Examples of regularization techniques include L1 and L2 regularization (Ridge regression and Lasso), dropout, and early stopping.

Do you have research experience in machine learning?

73

Tell us do you have research experience in machine learning?

149

What are standardization and normalisation? Give one advantage of each over the other?

74

Tell me what are the last machine learning papers you've read?

208