INTRODUCTION MACHINE LEARNING
INTRODUCTIONTOMACHINE LEARNINGAN EARLY DRAFT OF A PROPOSEDTEXTBOOKNils J. NilssonRobotics LaboratoryDepartment of Computer ScienceStanford UniversityStanford, CA 94305e-mail: 3, 1998Copyrightc 2005 Nils J. NilssonThis material may not be copied, reproduced, or distributed without thewritten permission of the copyright INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . is MACHINE LEARNING ? . . . . . . . . . . . . . . . . . of MACHINE LEARNING . . . . . . . . . . . . . . of MACHINE LEARNING . . . . . . . . . . . . . . . . LEARNING Input-Output Functions . . . . . . . . . . . . . . . . . . of LEARNING . . . . . . . . . . . . . . . . . . . . . . Vectors.
Chapter 1 Preliminaries 1.1 Introduction 1.1.1 What is Machine Learning? Learning, like intelligence, covers such a broad range of processes that it is dif-
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