Infopaket

Neural Networks

ДВС.1.03

Обов’язкова дисципліна для ОП

Second

2021/2022

3 Semester

4

Full-time form

1. To know: the basic disciplines - "Mathematical Analysis", "Linear Algebra and Geometry", "Probability Theory and Mathematical Statistics", "Programming", "Computational Geometry and Computer Graphics", "Algorithms and Data Structures", "Machine Learning" . 2. To be able to: develop, analyze and apply algorithms and software to solve problems and applied tasks using modern software development methods.

Discipline aim. The aim of the discipline is to acquaint students with the basics of convolutional neural networks as one of the main branches of artificial intelligence, and modern methods for solving problems of computer vision and image processing, including obtaining semantic and metric information from images. To prepare the student for the effective use of modern methods such as machine learning methods to create artificial intelligence systems in further professional activities; help to acquire skills of practical work with modern software for building intelligent models.

3. Dэvyd A. Forsait, Zhan Pons. Kompiuternoe zrenye. Sovremennыi podkhod, 2004 4. Lynda Shapyro, Dzhordzh Stokman. Kompiuternoe zrenye. Laboratoryia znanyi. 2013 5. Stephen Marsland. Machine Learning: An Algorithmic Perspective, 452 р., 2015. 6. Christopher M Bishop. Pattern recognition. Machine Learning, 128 p., 2006. 7. Ethem Alpaydin. Introduction To Machine Learning, 584 p., 2009. 8. Tom M. Mitchell. Machine Learning [http://www.cs.cmu.edu/~tom/mlbook.html] 9. Yaser S. Abu-Mostafa. Learning from data, 215 p., 2017 10. Alex Smola. Introduction to Machine Learning, 234 p., 2008. 11. Liuher Dzh.F. Yskusstvennыi yntellekt: stratehyy y metodы reshenyia slozhnыkh problem. – M.: Vyliams, 2005. – 864 s. 12. Trevor Hastie, Robert Tibshirani, Jerome Friedman. The Elements of Statistical Learning: Data Mining, Inference and Prediction, 764 p., 2008.

Lecture, Laboratory work, individual work

- semester examination: 1. Active work during a lection: PH1.1, PH1.2, PH1.3, PH1.4; 2. Execution of individual tasks: PH2.1, PH2.2, PH2.3; 3. Test 1: PH1.1, PH1.2; 4. Test 2: PH1.3; 5. Test 3: PH1.4; - final examination: final test. - maximum: 40 points; - studying results for examination: PH1.1, PH1.2, PH1.3, PH1.4; - task form: writing.

Ukrainian language