Machine Learning

Major: Computer Sciences
Code of subject: 7.122.04.O.68
Credits: 5.00
Department: Artificial Intelligence Systems
Lecturer: Boyko N.I.
Semester: 1 семестр
Mode of study: денна
Learning outcomes: As a result of the study of the discipline, the student should be able to demonstrate the following learning outcomes: to know: application areas and basic applied aspects of machine learning; basic concepts and principles of work of artificial neural networks; problem statement and basic natural language processing methods; be able to: correctly formulate the tasks that arise in the practical activity, to solve them by means of machine learning methods; to analyze a specific problem in order to select the best method of machine learning for its solution; to carry out the analysis and synthesis of informative features; to analyze the work of machine learning methods to identify their strengths and weaknesses
Required prior and related subjects: Discrete Math Mathematical analysis Linear algebra Probability theory Mathematical statistics
Summary of the subject: The purpose of studying the discipline is to obtain the necessary knowledge and to acquire practical skills in applying a wide range of methods and algorithms for analyzing information in the context of machine perception and learning to understand the issues of building, operating and operating computer systems and networks, as well as various information processing and control systems basis.
Assessment methods and criteria: Current control Laboratory work 40 points Examination control Written component of 60 points Oral component 0 points Total 100 points
Recommended books: Stephen Marsland. Machine Learning). 452 р.,2015. Ethem Alpaydin. Introduction To Machine Learning)., 584 p., 2009. Tom M. Mitchell. Machine Learning). [http://www.cs.cmu.edu/~tom/mlbook.html] Yaser S. Abu-Mostafa. Learning). 215 p., 2017