Advanced Optimization Techniques in AI By A Staff Writer / July 10, 2025 Welcome to your Advanced Optimization Techniques in AI Level: Expert What is the purpose of gradient descent in optimization? To add more features to the dataset To minimize the loss function by updating parameters iteratively To visualize datasets To reduce computational time None Which variation of gradient descent uses the entire dataset to calculate gradients? Stochastic Gradient Descent Batch Gradient Descent Mini-batch Gradient Descent Momentum None What is the primary advantage of the Adam optimizer over basic gradient descent? It requires no hyperparameter tuning It adjusts learning rates dynamically for each parameter It simplifies model complexity It eliminates overfitting None Which regularization technique penalizes large weights in a model? Dropout L2 Regularization (Ridge) Gradient Clipping Batch Normalization None What is the purpose of hyperparameter tuning? To adjust internal model parameters To find the optimal combination of external settings for the best performance To reduce data size To eliminate overfitting None Time's up
