Lecture1 - Machine Learning

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Lecture1 - Machine Learning

  1. 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. 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 Slide 2 Artificial Intelligence Machine Learning
  3. 3. Today’s Agenda Administrivia Goals of the course: yours and mine The Project Slide 3 Artificial Intelligence Introduction to C++
  4. 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 Slide 4 Artificial Intelligence Machine Learning
  5. 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 Slide 5 Artificial Intelligence Machine Learning
  6. 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 Slide 6 Artificial Intelligence Machine Learning
  7. 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 Slide 7 Artificial Intelligence Machine Learning
  8. 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 Slide 8 Artificial Intelligence Machine Learning
  9. 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 Slide 9 Artificial Intelligence Introduction to C++
  10. 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 Slide 10 Artificial Intelligence Machine Learning
  11. 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

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