Chapter 1 - Artificial Neural Network Fundamentals

1. What are the various layers in a neural network?
   Input, Hidden, and Output Layers
2. What is the output of a feed-forward propagation?
   Predictions that help in calculating loss value
3. How is the loss function of a continuous dependent variable different from that of a binary dependent variable and also of a categorical dependent variable?
   MSE is the generally used loss function for a continuous dependent variable and binary cross-entropy for a binary dependent variable. Categorical cross-entropy is used for categorical dependent variables.
4. What is stochastic gradient descent?
   It is a process of reducing loss, by adjusting weights in the direction of decreasing gradient
5. What does a backpropagation exercise do?
   It computes gradients of all weights with respect to loss using the chain rule
6. How does the weight update of all the weights across layers happen during back-propagation?
   It happens using the formula dW = W – alpha*(dW/dL)
7. What...