CSC 4510 – Machine Learning

Dr. Mary-Angela Papalaskari Department of Computing Sciences Villanova University

Course website: www.csc.villanova.edu/~map/4510/

Introduction

CSC 4510 - M.A. Papalaskari - Villanova University

Machine Learning

CSC 4510 - M.A. Papalaskari - Villanova University

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What is Learning?

• Herbert Simon (1970): “Learning is any process by which a system improves performance from experience.”

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What is Machine Learning?

• Arthur Samuel (1959): Machine Learning: Field of study that gives computers the ability to learn without being explicitly programmed.

Why Study Machine Learning? Engineering Better Computing Systems

•  Develop systems that are too difficult/expensive to program explicitly because they require specific detailed skills or knowledge tuned to a specific task –  Personalized news or mail filter –  Personalized tutoring

SPAM CSC 4510 - M.A. Papalaskari - Villanova University

Why Study Machine Learning? Cognitive Science

•  Computational studies of learning may help us understand learning in humans and other biological organisms. –  Hebbian neural learning

•  “Neurons that fire together, wire together.” –  Human’s relative difficulty of learning disjunctive

concepts vs. conjunctive ones. –  Power law of practice

log(# training trials)

log(

perf.

tim

e)

CSC 4510 - M.A. Papalaskari - Villanova University

Why Study Machine Learning? The time is ripe

•  Large amounts of computational resources available. •  Many basic effective and efficient algorithms available. •  The world is driven by data (data mining).

–  Market basket analysis (e.g. diapers and dvds) –  News aggregation –  Over 50m credit card transactions a day in the US alone. –  The Large Hadron Collider produces 60 gigabytes per minute –  Climate research centres generate 1-20 petabytes per year –  Google processes 24 petabytes per day

CSC 4510 - M.A. Papalaskari - Villanova University

So, um, what’s a petabyte again?

CSC 4510 - M.A. Papalaskari - Villanova University

Humans can: - think, learn, see, understand language, reason, etc.

Artificial Intelligence aims to reproduce these capabilities. Machine Learning is one part of Artificial Intelligence.

Artificial Intelligence Statistics / Mathematics

Computer Vision

Data Mining

Machine Learning

Robotics

CSC 4510 - M.A. Papalaskari - Villanova University

Let’s try something

•  You will be given instructions in class to collect data about your classmates

•  Enter these data in the document provided •  We will use the decision tree algorithm

from aispace.org/ to “learn” something about your sample

CSC 4510 - M.A. Papalaskari - Villanova University

Next time

•  Some historical background on AI and a more careful definition of machine learning

•  Discussion of Alan Turing article: “Computing Machinery and Intelligence” http://loebner.net/Prizef/TuringArticle.html

•  See also: •  Alan Turing website maintained by Andrew Hodges:

http://www.turing.org.uk/turing/ •  Philosophical objections to Turing Test

http://plato.stanford.edu/entries/chinese-room/

Some of the slides in this presentation are adapted from: •  Prof. Frank Klassner’s ML class at Villanova •  the University of Manchester ML course http://www.cs.manchester.ac.uk/ugt/COMP24111/ •  The Stanford online ML course http://www.ml-class.org/ CSC 4510 - M.A. Papalaskari - Villanova University