Course unit code:
Course unit title:
Introduction to machine learning
Mode of completion and Number of ECTS credits:
Class req (2 credits)
Course supervisor:
doc. Ing. MSc. Martin Klaučo, PhD.
Name of lecturer(s):
K. Kiš (2021/2022 – Winter)
Learning outcomes of the course unit:
By completing this course, the student acquired basic knowledge about methods of machine learning. The student also acquired practical skills in data analysis and graphical interpretation using the Python programming language. By completing the course, the student is competent in the design of advanced regression and classification models of different datasets.
Prerequisites for registration:
Course contents:
Recommended or required reading:
  • Guido, S.: Introduction to Machine Learning with Python, O'Reilly Media, Inc, USA, 2016, ISBN: 9781449369415
  • Chollet, F.: Deep Learning with Python, Manning Publications, 2017, ISBN: 1617294438
  • McKinney, W.: Python for Data Analysis, 2nd edition, O'Reilly Media, Inc, USA, 2017, ISBN: 9781491957660
Planned learning activities and teaching methods:
Contact teaching: exercises 26h Contactless teaching: preparation for exercises (12h), preparation of final project (12h)
Assesment methods and criteria:
Evaluation is based 50% on the work during the semester, 50% from the final project evaluation. The rating is based on the standard FCHPT scale.
Language of instruction:
Slovak, English
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