P034 Machine Learning

Faculty of Informatics
Autumn 1998
Extent and Intensity
2/0. 2 credit(s). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
Teacher(s)
doc. Ing. Jan Žižka, CSc. (lecturer)
Guaranteed by
Contact Person: doc. Ing. Jan Žižka, CSc.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Syllabus
  • Machine Learnig (ML) as the integration of Artificial Intelligence (AI) and cognitive sciences. Computational processes that are related to learning. Selection of learning algorithms.
  • Training and testing data. Solution space. Learning and searching. Natural and human learning. Problem representation language. Learning algorithms with numerical and symbolic inputs.
  • Perceptrons, logical neural networks, Boltzmann machine, Kohonnen maps. Genetic algorithms. Comparison with biological systems.
  • Methods of decision-tree induction. Presence of noise, incomplete description of examples. Utilization of knowledge and the possibility of transformation from decision trees to rules.
  • Pattern recognition. Generalisation. The method of a nearest neighbour (k-NN). Instance-based learnig (IBL). Radial basis functions (RBF).
  • Learning in rule-based systems. Inductive and EBL (deductive) learning.
  • Other learning methods. Reinforcement learning.
  • Mathematical aspects of learning. PAC, VC-dimension, Occam's razor.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
The course is also listed under the following terms Autumn 1995, Autumn 1996, Autumn 1997, Autumn 1999, Autumn 2000, Autumn 2001.
  • Enrolment Statistics (Autumn 1998, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn1998/P034