INTRODUCTION MACHINE LEARNING

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INTRODUCTION . TO. MACHINE LEARNING . AN EARLY DRAFT OF A PROPOSED. TEXTBOOK. Nils J. Nilsson Robotics Laboratory Department of Computer Science Stanford University Stanford, CA 94305. e-mail: November 3, 1998. Copyright 2005. c Nils J. Nilsson This material may not be copied, reproduced, or distributed without the written permission of the copyright holder. ii Contents 1 Preliminaries 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. What is MACHINE LEARNING ? . . . . . . . . . . . . . . . . . 1. Wellsprings of MACHINE LEARNING .

rience," and \modi cation of a behavioral tendency by experience." Zoologists and psychologists study learning in animals and humans. In this book we fo-cus on learning in machines. There are several parallels between animal and machine learning. Certainly, many techniques in machine learning derive from

  Machine, Learning, Experience, Machine learning