1. Introduction to Machine
Learning
Lecture 1
Albert Orriols i Puig
aorriols@salle.url.edu
i l @ ll ld
Artificial Intelligence – Machine Learning
Enginyeria i Arquitectura La Salle
gy q
Universitat Ramon Llull

2. Where Are We?
Knowledge
Kno ledge
Search
representation
We have seen several search techniques:
Blind search, heuristic search, adversary search … GAs
We have seen several ways of representing our
knowledge
Logic-based representation, rule-based representation …
g p p
We have discussed reasoning mechanisms to deal with
uncertainty, incompleteness and inconsistency
y p y
We set the basis. But, the most interesting is still missing
Machine learning
M hi l i
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Artificial Intelligence Machine Learning

3. Today’s Agenda
Administrivia
Goals of the course: yours and mine
The Project
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Artificial Intelligence Introduction to C++

4. Administrivia
How will this course work?
Explanations based on lectures
Lectures will b released online
Lt ill be l d li
Each lecture
introduces a new problem and algorithms to solve it
has a set of related papers in the estudy
So, each lecture is complemented in the estudy!
Grade = 0.3 Theory + 0.7 PROJECT
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Artificial Intelligence Machine Learning

5. Administrivia
Syllabus of the course
Introduction to the paradigms in machine learning
How to solve real-world problems?
Data classification: C4.5, kNN, Naïve Bayes …
Statistical learning: SVM
Association analysis: A-priori
Link mining: Page Rank
Clustering: k-means
Reinforcement learning: Q-learning, XCS
Regression
Genetic Fuzzy Systems
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Artificial Intelligence Machine Learning

6. Goals: Yours & Mine
Your goal: pass the subject and graduate
g p j g
Be more specific. We would like to learn
What machine learning (ML) is about
What engineers can do to help scientists, businessmen, and
industry in g
y general with ML
Professional future in machine learning
My goal: I want you to
Be able to read literature
Understand machine learning as a pool of methods that solve
problems that are actually important nowadays
Forget about math and go on solving problems
Be able to conduct and present original research on the field
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Artificial Intelligence Machine Learning

7. The Project
70% of PROJECT to accomplish my g
p y goal …
… be able to conduct and present original research on the field
How will it work?
H ill k?
Wait until having seen the introduction to ML
Select a line in which you want to work
Data classification
Statistical learning
Association analysis
Link mining
Clustering
Reinforcement learning
Define an objective
Work toward this objective
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Artificial Intelligence Machine Learning

8. Requirements of the Project
You must satisfy
Select a topic and a goal before February 23
Develop the p j
p project:
Use a computer language of your choice
Present the project at class on May
pj y
Write a technical report
Deadline: May 28, 2009
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Artificial Intelligence Machine Learning

9. Next Class
What’s Machine Learning?
Why Machine Learning?
Paradigms of Machine Learning
How I Would Like my Problem to Look Like?
Summary of the Paradigms that we Won’t Study
Won t
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Artificial Intelligence Introduction to C++

10. Acknowledgments
Part of the lectures borrowed from
Francisco Herrera Triguero
F i H Ti
Head of Research Group SCI2S
(Soft Computing and Intelligent Information Systems)
Department of Computer Science and Artificial Intelligence
ETS de Ingenierias Informática y de Telecomunicación
University of Granada, E-18071 Granada, Spain
Tel: +34-958-240598 - Fax: +34-958-243317
34 958 240598 34 958 243317
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Artificial Intelligence Machine Learning

11. Introduction to Machine
Learning
Lecture 1
Albert Orriols i Puig
aorriols@salle.url.edu
i l @ ll ld
Artificial Intelligence – Machine Learning
Enginyeria i Arquitectura La Salle
gy q
Universitat Ramon Llull