# **Machine Learning**

**UNIT 3**

**Important Questions**

1) What is Artificial Neural Network?

2) What is the type of problems in which Artificial

Neural Network can be applied.

3) Explain the concept of a Perceptron with a neat

diagram.

4) Discuss the Perceptron training rule.

5) Under what conditions the perceptron rule fails

and it becomes necessary to apply the delta rule

6) What do you mean by Gradient Descent?

7) Derive the Gradient Descent Rule.

8) What are the conditions in which Gradient

Descent is applied.

9) What are the difficulties in applying Gradient

Descent.

10)Differentiate between Gradient Descent and

Stochastic Gradient Descent

11)Define Delta Rule.

12)Derive the Backpropagation rule considering the

training rule for Output Unit weights and Training Rule for Hidden Unit weights

13)Write the algorithm for Back propagation.

14) Explain how to learn Multilayer Networks using

Gradient Descent Algorithm.

15)What is Squashing Function?