1 machine learning 1.where does machine learning fit in computer science? 2.what is machine...

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Machine LearningMachine Learning

1.1. Where does machine learning fit in computer science?Where does machine learning fit in computer science?

2.2. What is machine learning?What is machine learning?

3.3. Where can machine learning be applied?Where can machine learning be applied?

4.4. Should I care about machine learning at all?Should I care about machine learning at all?

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Where does machine learning fit in computer Where does machine learning fit in computer science? science?

Search

Artificial Intelligence

Planning Knowledge

Representation

Machine Learning Robotics

Clustering

Classification

Genetic Algorithms

Reinforcement

Learning

Field of Study

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Where does machine learning fit in computer Where does machine learning fit in computer science? (2)science? (2)

MachineMachineLearningLearning

Probability &Probability &StatisticsStatistics

ComputationalComputationalComplexityComplexity

TheoryTheory InformationInformationTheoryTheory

PhilosophyPhilosophy

NeurobiologyNeurobiology

ArtificialArtificialIntelligenceIntelligence

Multidisciplinary FieldMultidisciplinary Field

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Where does machine learning fit in Where does machine learning fit in computer science? (3)computer science? (3)

Selection

Target Data

Preprocessing

Data Preprocessed Data

Transformation

Transformed Data

PatternsData Mining

Interpretation & EvaluationKnowledge

Knowledge Discovery and Data Mining

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1.1. Where does machine learning fit in computer science?Where does machine learning fit in computer science?

2.2. What is machine learning?What is machine learning?

3.3. Where can machine learning be applied?Where can machine learning be applied?

4.4. Should I care about machine learning at all?Should I care about machine learning at all?

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• Where does machine learning fit in computer science?Where does machine learning fit in computer science?

• What is machine learning?What is machine learning?

• DefinitionDefinition

• Types of Machine LearningTypes of Machine Learning

• Where can machine learning be applied?Where can machine learning be applied?

• Should I care about machine learning at all?Should I care about machine learning at all?

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What is Machine Learning?What is Machine Learning?DefinitionDefinition

Machine learning is the study of how to make computers Machine learning is the study of how to make computers learn or adapt; the goal is to make computers improve their learn or adapt; the goal is to make computers improve their performance through experience.performance through experience.

Experience Experience EE

ComputerComputer

LearningLearning

AlgorithmAlgorithm

Class of Tasks Class of Tasks TT PerformancePerformance PP

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What is Machine Learning? What is Machine Learning? Definition (2)Definition (2)


ComputerComputer

LearningLearning

AlgorithmAlgorithm


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It is the kind of activity on which the computer will learn to It is the kind of activity on which the computer will learn to improve its performance. Examples: improve its performance. Examples:

Learning to Learning to Play chess Play chess

Recognizing Recognizing Images of Images of

Handwritten Handwritten WordsWords

Diagnosing Diagnosing patientspatients

coming into thecoming into the hospitalhospital

Class of Tasks:Class of Tasks:

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ComputerComputer

LearningLearning

AlgorithmAlgorithm


1111


ExperienceExperience: What has been recorded in the past: What has been recorded in the past

PerformancePerformance: A measure of the quality of the response or action. : A measure of the quality of the response or action.

Example: Example: Handwritten recognition using Neural NetworksHandwritten recognition using Neural Networks

ExperienceExperience: a database of handwritten images : a database of handwritten images with their correct classification with their correct classification

PerformancePerformance: Accuracy in classifications: Accuracy in classifications

Experience and PerformanceExperience and Performance

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ComputerComputer

LearningLearning

AlgorithmAlgorithm


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Example: Diagnosing a patient coming into the hospital.Example: Diagnosing a patient coming into the hospital.

Features:Features: XX11: Temperature: Temperature XX22: Blood pressure: Blood pressure XX33: Blood type: Blood type XX44: Age: Age XX55: Weight: Weight Etc.Etc.

Given a new example X = < xGiven a new example X = < x11, x, x22, …, x, …, xnn > >

F(X) = wF(X) = w11xx11 + w + w22xx22 + w + w33xx33 = … + w = … + wnnxxnn

If F(X) > T predict If F(X) > T predict heart diseaseheart disease otherwise predict otherwise predict no heart diseaseno heart disease

The Representation of the Target Knowledge

Designing a Learning SystemDesigning a Learning System

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• DefinitionDefinition

• Types of Machine LearningTypes of Machine Learning



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What is Machine Learning?What is Machine Learning?Types of Machine LearningTypes of Machine Learning

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning

• Evolutionary Learning

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What is Machine Learning?What is Machine Learning?Types of Machine Learning (2)Types of Machine Learning (2)

Supervised LearningSupervised Learning

Each example or object has a class attached to it.Each example or object has a class attached to it. We try to learn a mapping from examples to classes.We try to learn a mapping from examples to classes.

Two modes: classification and regressionTwo modes: classification and regression

Machine learning algorithms abound:Machine learning algorithms abound: Decision Trees Decision Trees Rule-based systemsRule-based systems Neural networksNeural networks Nearest-neighborNearest-neighbor Support-Vector MachinesSupport-Vector Machines Bayesian MethodsBayesian Methods

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What is Machine Learning? What is Machine Learning? Types of Machine Learning (2) Types of Machine Learning (2)

Supervised Learning – Neural NetworksSupervised Learning – Neural Networks

Artificial Neural NetworksArtificial Neural Networks are crude attempts to model the highly massive are crude attempts to model the highly massive parallel and distributed processing we believe takes place in the brain. parallel and distributed processing we believe takes place in the brain.

Consider: Consider: 1)1) the speed at which the brain recognizes images; the speed at which the brain recognizes images; 2)2) the many neurons populating a brain; the many neurons populating a brain; 3)3) the speed at which a single neuron transmits signals. the speed at which a single neuron transmits signals.

Brain

NeuronModel Representation

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What is Machine Learning?What is Machine Learning? Types of Machine Learning (2) Types of Machine Learning (2)

Supervised Learning – Neural Networks(2)Supervised Learning – Neural Networks(2)

Input nodesInput nodes

Internal nodesInternal nodes

Output nodesOutput nodes

Left Left StraightStraight RightRight

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Unsupervised LearningUnsupervised Learning

Examples or objects have no class attached to them.Examples or objects have no class attached to them.

From “Pattern Classification” by Duda, Hart and Stork, 2nd Ed. Wiley Interscience (2000)

2020

What is Machine Learning? What is Machine Learning? Types of Machine Learning (4) Types of Machine Learning (4)

Reinforcement LearningReinforcement Learning

Supervised Learning:

Example Class

Reinforcement Learning:

Situation Reward Situation Reward

…

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Evolutionary LearningEvolutionary Learning

Methods inspired by the process of biological evolution.

Main ideas

Population of solutions

Assign a score orfitness value to each solution

Retain the bestsolutions (survival of the fittest)

Generate newsolutions (offspring)

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Where can machine learning be applied?Where can machine learning be applied?Application 1Application 1

Automatic car drive (ALVINN 1989)

Train computer-controlled vehicle to steer correctly when

driving on a variety of road types.

computer

(learning algorithm)

class 1

steer to the left

class 2

steer to the right

class 3

continue straight

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Where can machine learning be applied? Where can machine learning be applied? Application 1 (2)Application 1 (2)

Automatic Car DriveAutomatic Car Drive

Class of TasksClass of Tasks: : Learning to drive on highways from Learning to drive on highways from

vision stereos.vision stereos.

KnowledgeKnowledge: : Images and steering commands recorded Images and steering commands recorded while observing a human driver.while observing a human driver.

Performance ModulePerformance Module: Accuracy in classification : Accuracy in classification

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Where can machine learning be applied? Where can machine learning be applied? Application 2Application 2

Learning to classify astronomical structures.Learning to classify astronomical structures.

galaxygalaxy

starsstars

Features:Features:o ColorColoro SizeSizeo MassMasso TemperatureTemperatureo LuminosityLuminosity

unkownunkown

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Where can machine learning be applied? Where can machine learning be applied? Application 2 (2)Application 2 (2)

Classifying Astronomical ObjectsClassifying Astronomical Objects

Class of TasksClass of Tasks: : Learning to classify new objects.Learning to classify new objects.

KnowledgeKnowledge: : database of images with correct database of images with correct classification.classification.

Performance ModulePerformance Module: Accuracy in classification : Accuracy in classification

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Where can machine learning be applied? Where can machine learning be applied? Other Applications Other Applications

Bio-TechnologyBio-Technology Protein Folding Prediction Protein Folding Prediction Micro-array gene expressionMicro-array gene expression

Computer Systems Performance PredictionComputer Systems Performance Prediction Banking ApplicationsBanking Applications

Credit ApplicationsCredit Applications Fraud DetectionFraud Detection

Character Recognition (US Postal Service)Character Recognition (US Postal Service) Web ApplicationsWeb Applications

Document ClassificationDocument Classification Learning User PreferencesLearning User Preferences

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Should I care about Machine Learning at all?Should I care about Machine Learning at all?

Yes, you should!Yes, you should!

Machine learning is becoming increasingly popular and has become a Machine learning is becoming increasingly popular and has become a cornerstone in many industrial applications.cornerstone in many industrial applications.

Machine learning provides algorithms for data mining, where the goal Machine learning provides algorithms for data mining, where the goal is to extract useful pieces of information (i.e., patterns) from large is to extract useful pieces of information (i.e., patterns) from large databases. databases.

The computer industry is heading towards systems that will be able to The computer industry is heading towards systems that will be able to adapt and heal themselves automatically. adapt and heal themselves automatically.

The electronic game industry is now focusing on games where The electronic game industry is now focusing on games where characters adapt and learn through time.characters adapt and learn through time.

NASA is interested in robots able to adapt in any environment NASA is interested in robots able to adapt in any environment autonomously.autonomously.

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SummarySummary

Machine learning is the study of how to make computers learn.Machine learning is the study of how to make computers learn.

A learning algorithm needs the following elements: A learning algorithm needs the following elements: class of tasks, class of tasks, performance metric, and body of experience. performance metric, and body of experience.

The design of a learning algorithm requires to define the The design of a learning algorithm requires to define the knowledge to knowledge to learn, the representation of the target knowledge, and the learning learn, the representation of the target knowledge, and the learning mechanism.mechanism.

Machine learning counts with many successful applications and is Machine learning counts with many successful applications and is becoming increasingly important in science and industry.becoming increasingly important in science and industry.

1 machine learning 1.where does machine learning fit in computer science? 2.what is machine...

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