A. I. Cuza University of Iaşi

Advanced Artificial Intelligence

Course nameAdvanced Artificial Intelligence CodeMSD1205
Class Master of Distributed Systems, 2009 - 2011
Level Master Year 1 Semester 2 Status Compulsory
Hours per weekTotal hours per semesterTotal hours of individual workCreditsEvaluation typeTeaching language
CSLPr
2 0 2 0 56 184 8 E ro
Taught byAcademic and scientific title, name
Associate Professor, PhD, Liviu Ciortuz
Required courses
ObjectivesUnderstanding the conception and practical usage of the most important algorithms for classification and clustering.
General thematics
  1. Fundamental Concepts in Machine Learning
  2. Decision Trees
  3. Instance-based Learning
  4. Neural Networks
  5. Bayesian Learning
  6. Support Vector Machines
  7. Evaluating Hypotheses
  8. Clustering Algorithms
  9. Reinforcement Learning
  10. Boosting, bagging, random forests, voting, co-training
Seminary / Laboratory thematicsSolving problems and exercises
Implementation of some of the presented algorithms and their applications
Presentation of recent papers in the area of machine learning:
String kernels and applications
Ranking algorithms
Teaching methodsSlides on video-projector.
Bibliography
  • „Machine Learning”, Tom Mitchell; McGraw-Hill, 1997
  • „Support Vector Machines and other kernel-based methods”, Nello Cristianini, John Shawe-Taylor, Cambridge University Press, 2000
  • „Foundations of Statistical Natural Language Processing”, Christopher Manning, Hinrich Schuetze; MIT Press, 2002 (ch. 2 and 14)
Evaluationconditions
criterias
modes
formulaBasis (1 point) +  1st written work (4.5 points)  +  2nd written work  (4.5 points)
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