Machine Learning

  NN : Introduction to Neural Network Q1. Weights impact For the neural network shown above, which of these statements is true? Choose the correct answer from below: A.     -5 weight is bad for the neural network. B.     The neuron with weight 10 will have the most impact on the output. C.     The neuron with weight -5 will have the most impact on the output. D.     The neuron with weight 2 will have the most impact on the output. Ans: B Correct option :  The neuron with weight 10 will have the most impact on the output. Explanation : There is no such thing that a neuron with a negative weight will be bad for the output. The negative or positive weight of a neuron simply means whether it has an increasing or decreasing effect on the output value. A neuron with the largest magnitude will have the most significant effect on the output value.   Q2. Calculate Forward Pass The neuron  n  has the weights 1,2,3,4, and 5. The values of inputs are 4,10,5,20, and 0.

  UNIT-1 Deep Learning: Fundamentals Short Answer Questions ----------------------------------------------------------------------------------------------------------------------------- 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? 2