FI:P034 Machine Learning - Course Information
P034 Machine Learning
Faculty of InformaticsAutumn 1999
- Extent and Intensity
- 2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium), z (credit).
- Teacher(s)
- doc. Ing. Jan Žižka, CSc. (lecturer)
- Guaranteed by
- prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
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
- Informatics (programme FI, B-IN)
- Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
- Information Technology (programme FI, B-IN)
- 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.
- Enrolment Statistics (Autumn 1999, recent)
- Permalink: https://is.muni.cz/course/fi/autumn1999/P034