Answer Posted / Deepanshu Jetley

To avoid overfitting, techniques like cross-validation, regularization (L1 or L2), early stopping, and dropout can be used. Cross-validation helps assess the generalization performance of a model by evaluating it on multiple subsets of the data. Regularization adds a penalty term to the loss function to discourage complex models with too many parameters. Early stopping stops training once the validation error starts increasing, indicating overfitting.

Tell us do you have research experience in machine learning?

149

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

208

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

74

Do you have research experience in machine learning?

73