PDF4PRO ⚡AMP

Modern search engine that looking for books and documents around the web

Example: quiz answers

INTRODUCTION MACHINE LEARNING - Stanford University

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 .. 3. Varieties of MACHINE LEARNING .. 4. LEARNING Input-Output Functions .. 5. Types of LEARNING .. 5. Input Vectors .. 7. Outputs .. 8. Training Regimes .. 8. Noise .. 9. Performance Evaluation .. 9. LEARNING Requires Bias.

Preface These notes are in the process of becoming a textbook. The process is quite un nished, and the author solicits corrections, criticisms, and suggestions from

Loading..

Tags:

  Machine, Learning, Machine learning

Information

Domain:

Source:

Link to this page:

Please notify us if you found a problem with this document:

Spam in document Broken preview Other abuse

Transcription of INTRODUCTION MACHINE LEARNING - Stanford University

Related search queries