Table of Contents

Deep Learning

This block course is read in the study program “Mathematical Methods of Computer Vision and Pattern Recognition” of the National Technical University of Ukraine, Institute of Physics and Technology in summer semester 2019


This course introduces fundamentals of deep learning and related concepts of machine learning



* Teacher: Boris Flach (Czech Technical University in Prague)

* Prerequisites:

  • probability theory and statistics
  • pattern recognition and decision theory
  • linear algebra and optimisation

* Schedule: The course will take place in the week April, 9-12 in the room 305-2, building 1

* Grading: exam conversation at the end of the course on April, 12 starting at 12:20

* Literature:

  • Shai Shalev-Shwartz, Shai Ben-David, Understanding Machine Learning: From Theory to Algorithms, Cambridge University press, 2014
  • Ian Goodfellow and Yoshua Bengio and Aaron Courville, Deep Learning, MIT Press, 2016

* Materials:

misc/dlk19/start.txt · Last modified: 2019/03/29 14:41 by flachbor