Machine Learning UNIT - 1 SYLLABUS

UNIT - I 

 Introduction

 1. Well-Posed Learning Problems

 2. Designing a Learning System 

 3. Perspectives and Issues in Machine Learning 

 4. Introduction to Supervised, Unsupervised and Reinforcement Learning.

 Concept Learning and the General to Specific Ordering 

 5. Introduction

 6. A Concept Learning Task 

 7. Concept Learning as Search 

 8. Find-S: Finding a Maximally Specific Hypothesis 

 9. Version Spaces and the Candidate Elimination Algorithm.

MACHINE LEARNING UNIT- 5 (B) NOTES (REINFORCEMENT LEARNING)

MACHINE LEARNING UNIT-5(B) PPT's (Reinforcement Learning)

MACHINE LEARNING UNIT-5 (A) NOTES (ANALYTICAL LEARNING)

MACHINE LEARNING UNIT-5(A) PPT's (Analytical Learning)

MACHINE LEARNING UNIT-4(A) PPT's (Genetic Algorithms)

MACHINE LEARNING UNIT-4 (B) PPT's (Learning Sets of Rules)