machine learning an introduction. what is learning? herbert simon: “learning is any process by...

Machine Learning

An Introduction

What is Learning? Herbert Simon: “Learning is any process by

which a system improves performance from experience.”

What is the task? Classification Problem solving / planning / control

Classification Assign object/event to one of a given finite set of

categories. Medical diagnosis Credit card applications or transactions Fraud detection in e-commerce Worm detection in network packets Spam filtering in email Recommended articles in a newspaper Recommended books, movies, music, or jokes Financial investments DNA sequences Spoken words Handwritten letters Astronomical images

Problem Solving / Planning / Control Performing actions in an environment in

order to achieve a goal. Solving calculus problems Playing checkers, chess, or backgammon Balancing a pole Driving a car or a jeep Flying a plane, helicopter, or rocket Controlling an elevator Controlling a character in a video game Controlling a mobile robot

Learning from DataThe world is driven by data.

Germany’s climate research centre generates 10 petabytes per year Google processes 24 petabytes per day The Large Hadron Collider produces 60 gigabytes per minute (~12

DVDs) There are over 50m credit card transactions a day in the US alone.

Learning from Data

Data is recorded from some real-world phenomenon. What might we want to do with that data?

Prediction - what can we predict about this phenomenon?

Description - how can we describe/understand this phenomenon in a

new way?

Learning from Data

How can we extract knowledge from data to help humans take decisions?

How can we automate decisions from data?

How can we adapt systems dynamically to enable better user experiences?

Write code to explicitlydo the above tasks

Write code to make the computerlearn how to do the tasks

Using machine learning to detect spam emails

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ALGORITHMNaïve BayesRule mining

Using machine learning to recommend books

ALGORITHMSCollaborative FilteringNearest NeighbourClustering

Using machine learning to identify faces and expressions

ALGORITHMSDecision Trees

Adaboost

Boundary Detection

Is this a boundary?

Image CategorizationTraining Labels

Training Images

Classifier

Training

Training

Image Features

Image Features

Testing

Test Image

Trained

Classifier

Trained Classifier Outdoor

Prediction

Slide: Derek Hoiem

ML for working with social network data ML for working with social network data: detecting

fraud, predicting click-thru patterns, targeted advertising, etc etc etc .

ALGORITHMSSupport Vector MachinesCollaborative filteringRule mining algorithmsMany many more….

ML for mobile

Machine Learning (etc.) Driving a car Recognising spam emails Recommending books Reading handwriting Recognising speech, faces, etc.

How would you write these programs?Would you want to?!?!?!?

Machine Learning Problems