Course detail

Machine Learning Fundamentals

FEKT-MPC-MLFAcad. year: 2020/2021

Quantum information is a basic entity in quantum information theory and can be manipulated using engineering techniques known as quantum information processing. As well as they can be processed by digital computers as classical information, transferred from place to place, manipulated and analyzed, similar concepts can be handled with quantum information. While the basic unit of classical information is a bit, in quantum information it is a qubit. Therefore, in computer exercises attention is paid to the processing of qubit.

Learning outcomes of the course unit

The graduate is able to: (a) understand quantum computer problems, specifically, it is able to recognize when such a calculation is advantageous; (b) calculate and design basic algorithms for quantum computers.

Prerequisites

Not applicable.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

GRUSKA, J., Quantum Computing (Advanced topics in computer science series), Osborne/McGraw-Hill, 1999. (EN)

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Not applicable.

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

1 - Organization of teaching, introduction to machine learning, motivation
2 - Basics of linear algebra for ML
3 - Support vectors, Support vector Machines
4 - Introduction to artificial neural networks, representation,
classification
5 - Neural network training (linear regression, Gradient method,
polynomial regression, ...)
6 - Convolutional neural networks
7 - Recursive neural networks
8 - Hyperparameter tuning, batch normalization and programming frameworks
9 - Learning without supervision
10 - Generative learning, autoencoders, GAN
11 - Machine learning on a large scale

Aims

The aim of the course is to acquaint students with basic concepts of quantum physics and algorithms necessary for working with quantum information. Quantum mechanics as a subject of physics examines how microscopic physical dynamic systems change in nature. However, in quantum information theory, quantum systems are studied as theoretical systems and concepts abstracted from quantum mechanics itself. The aim of computer exercises is to gain practical experience with the implementation of algorithms using quantum theory.

Classification of course in study plans

  • Programme MPC-EKT Master's, 2. year of study, summer semester, 3 credits, compulsory-optional

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Exercise in computer lab

13 hours, compulsory

Teacher / Lecturer

eLearning