Dr. Rambabu Pemula

  FUNDAMENTALS OF MACHINE LEARNING Unit – I Introduction andConcept Learning: Well-posed learning problems, designing a learning system Perspectives and issues in machine learning, Types of learning.  Concept learning task , Concept Learning as search through a hypothesis space, Finding maximally specific hypotheses, Version spaces and the candidate elimination algorithm, Inductive Bias 👉 UNIT-1 (A) Introduction Notes   👉 UNIT-1(B) Concept Learning PPTs 👉 UNIT-1 Introduction and Concept Learning Notes 👉 UNIT-1 Introduction and Concept Learning Long Answer Question Unit - II Decision Treelearning and Neural Network learning : Decision Tree representation and learning algorithm, appropriate problems for Decision Tree Learning, Hypothesis space search in Decision Tree Learning, Inductive bias in Decision Tree Learning: Occam’s razor, Issues in Decision Tree Learning.  Introduction to Neural Network Learning , Introduction to Perceptions, Perceptions, Introductio...

  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...