Deep Learning Quiz

What algorithm is commonly used in deep learning to calculate the gradient of the loss function with respect to each weight in a neural network?

Which optimization algorithm in machine learning adapts the learning rate for each parameter individually using first and second moment estimates?

What mathematical operation is essential for computing weight updates in neural networks and involves finding the slope of a function at a given point?

Which gradient-based optimization method updates weights by moving in the opposite direction of the gradient and is known for its simplicity?

What tensor operation is fundamental for transforming input data in neural networks and is used to combine weights and activations?

Which optimization algorithm in deep learning adjusts the learning rate using an exponentially decaying average of squared gradients to normalize updates?

What is the primary goal of neural network training in deep learning?

Which mathematical field provides the foundation for understanding tensors, eigenvalues, and matrix decompositions in deep learning?

What is the term for the function that measures how far the predicted output of a neural network is from the actual output?

Which term describes the process of adjusting model parameters iteratively to reduce errors in a neural network?