Machine Learning

Q1. Neuron Which of the following is true about a single artificial neuron? Choose the correct answer from below , please note that this question may have multiple correct answers A.      It is loosely inspired from biological neurons B.      It computes weighted sum C.       It applies an activation function D.      It is capable of performing multi class classification Ans: A,B,C Correct Options:- It is loosely inspired from biological neurons It computes weighted sum It applies an activation function Explanation:- The basic inspiration for artificaial neurons did come from biological neurons. Biological neurons form a network a network within themselves. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. A neuron does it’s computation in 2 steps: First it comput

  Q1. Backpropagation in MLP Which of the following options are true with respect to Backpropagation? Choose the correct answer from below, please note that this question may have multiple correct answers A.      In backpropagation, we calculate the error contribution of each neuron. B.      In backpropagation, we calculate the loss gradients with respect to inputs. C.       In backpropagation, we calculate the loss gradient with respect to weights and biases. D.      In backpropagation, we update the weights of neurons in each iteration. Ans: A, C,D Correct options : i) In backpropagation, we calculate the error contribution of each neuron. ii) In backpropagation, we calculate the loss gradient with respect to weights and biases. iii) In backpropagation, we update the weights of neurons in each iteration. Explanation : Only this statement is false “It is used to calculate the loss gradients with respect to inputs.” as we can’t update the inputs. All the other