Machine Learning

UNIT-1 (A) Introduction   Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning  

UNIT-1  Introduction & Concept Learning and the General to Specific Ordering   Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning  Concept Learning and the General to Specific Ordering: Introduction A Concept Learning Task Concept Learning as Search Find-S: Finding a Maximally Specific Hypothesis Version Spaces and the Candidate Elimination Algorithm 

  2. DESIGNING A LEARNING SYSTEM The basic design issues and approaches to machine learning are illustrated by designing a program to learn to play checkers, with the goal of entering it in the world checkers tournament 1. Choosing the Training Experience 2. Choosing the Target Function 3. Choosing a Representation for the Target Function 4. Choosing a Function Approximation Algorithm 1. Estimating training values 2. Adjusting the weights 5. The Final Design   1. Choosing the Training Experience •        The first design choice is to choose the type of training experience from which the system will learn. •        The type of training experience available can have a significant impact on success or failure of the learner. There are three attributes which impact on success or failure of the learner 1.      Whether the training experience provides direct or indirect feedback regarding the choices made by the performance system. For example, in checkers game: