Course: Introduction to Machine Learning

» List of faculties » PRF » KI
Course title Introduction to Machine Learning
Course code KI/USU
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Kubera Petr, RNDr. Ph.D.
Course content
unspecified

Learning activities and teaching methods
unspecified
Learning outcomes
Prerequisites
unspecified
KI/APR1
----- or -----
KI/PGL1

Assessment methods and criteria
unspecified
Recommended literature
  • Chollet, F. Deep learning v jazyku Python: knihovny Keras, Tensorflow. Přeložil Rudolf Pecinovský. Praha: Grada Publishing, 2019.
  • Müller, A. Ch., Guido S. Introduction to machine learning with Python: a guide for data scientists. Beijing: O´Reilly, 2016.
  • Raschka, S. (Blog and Web pages [online]). 2020..
  • Raschka, S., Mirjalili V. Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow. Second edition. Birmingham: Packt, 2017.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Information Sciences (double subject) (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Science Study plan (Version): Information Systems (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -
Faculty: Faculty of Science Study plan (Version): Information Sciences (double subject) (A14) Category: Informatics courses - Recommended year of study:-, Recommended semester: -