Dr. Rambabu Pemula

  Unit – II: Decision Tree learning and Neural Network learning Decision Tree learning 1.      Decision Tree representation and learning algorithm, 2.      appropriate problems for Decision Tree Learning, 3.      Hypothesis space search in Decision Tree Learning, 4.      Inductive bias in Decision Tree Learning: Occam’s razor, 5.      Issues in Decision Tree Learning. Introduction to Neural Network Learning , 1.      Introduction to Perceptions, 2.      Perceptions, 3.      Introduction to Gradient Descent 4.      Back propagation. 👉 UNIT-2 (A) Decision Tree Learning Notes   👉 UNIT-2 (A) Decision Tree Learning PPTs 👉 UNIT-2(A) Decision Tree Learning Long Answer Questions 👉 UNIT-2 (B) Introduction to Neural Network Learning Notes 👉 UNIT-2 (B) Introduction to Neural Network Learnin...

  NN : Forward and Back Propagation Q1. Sigmoid and softmax functions Which of the following statements is true for a neural network having more than one output neuron ? Choose the correct answer from below: A.     In a neural network where the output neurons have the sigmoid activation, the sum of all the outputs from the neurons is always 1. B.     In a neural network where the output neurons have the sigmoid activation, the sum of all the outputs from the neurons is 1 if and only if we have just two output neurons. C.     In a neural network where the output neurons have the softmax activation, the sum of all the outputs from the neurons is always 1. D.     The softmax function is a special case of the sigmoid function Ans: C Correct option :  In a neural network where the output neurons have the softmax activation, the sum of all the outputs from the neurons is always 1. Explanation : ...