UNIT-1
Deep Learning: Fundamentals
Short Answer Questions
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1.
Define
Artificial Neural Network.
2. Define Neuron.
3.
List the
operations performed by ANN layers.
4.
List the
different applications of Deep Learning.
5.
Define
Deep Learning.
6.
List the
different applications of Artificial Neural Network.
7.
List the Building
Block of Neural Networks.
8.
Define
Dense layer.
9.
What is
loss function.
10. Identify the different layers in ANN.
11. Explain Forward Pass.
12. Explain Backward Pass.
13. List the different optimizers.
14. How to overcome vanishing and exploding
gradient problems
15. List the difficulties in convergence.
16. Define Preprocessing.
17. Define Momentum.
18. What is Learning Rate Decay?
19. What is the purpose of weight initialization?
20. What is Regularization?
21. List different Regularization techniques.
22. Define Dropout.
23. Define SoftMax activation function.
24. When we use cross entropy loss function?
25. List the different activation functions.
26. Define sigmoid activation function.
27. Define tanh activation function.
28. Define ReLU activation function.
29. How to train the neural network?
30.
Compare the ReLU
activation function with the sigmoid activation function.
