Deep Learning Quiz 1

1. The McCulloch-Pitts neuron, a foundational concept in neural networks, is characterized by which of the following?

2. What is the primary purpose of the backpropagation algorithm in training a Feed Forward Neural Network?

3. Which issue is Batch Normalization primarily designed to address during the training of deep neural networks?

4. In the context of dimensionality reduction, how does a basic, undercomplete autoencoder's approach relate to Principal Component Analysis (PCA)?

5. Which gradient descent optimization algorithm combines the concepts of Momentum and RMSProp?

6. A Denoising Autoencoder is trained to reconstruct the original, clean input after it has been fed a corrupted version of that input. What is the primary benefit of this approach?

7. What is a key difference between a standard autoencoder and a Variational Autoencoder (VAE)?

8. In a deep feedforward network, if the weights are all initialized to the same value (e.g., zero or a constant), what problem will occur during training?

9. Which of the following is a common form of dataset augmentation for image data?

10. What distinguishes Nesterov Accelerated Gradient (NAG) from classical Momentum-based Gradient Descent?