Data Mining Algorithms

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Applied Mathematics

Synopsis:

The course focuses on algorithms used in the fields of machine learning and data mining. However, this is not an introductory course, and the students should know machine learning basics. The emphasis is put on advanced algorithms (e.g., gradient boosting) and non-basic kinds of machine learning tasks (e.g., recommendation systems) and models (e.g., kernel methods).

Requirements:

Statistics, algorithmization, BIE-VZD - Introduction to data mining.

Syllabus of lectures:

1. Recalling basic data mining methods and their applications.

2. Model evaluation.

3. Bias-variance decomposition, negative correlation learning.

4. Decision trees and ensemble methods based on them.

5.-6. (2) Boosting and gradient boosting (XGBoost).

7. Introduction to kernel methods.

8. Kernel methods.

9. Modern kernel methods.

10. - 11. (2) Introduction to recommendation systems, usage of kNN.

12. Matrix factorisation for reccomendation.

13. Hyperparameters tuning, AutoML, new trends.

Syllabus of tutorials:

Study Objective:

Study materials:

[1] Hastie T.,Tibshirani R.,Friedman J., The Elements of Statistical Learning, Data Mining, Inference and Prediction, Springer, 2011

[2] Murphy, K. P., Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series), The MIT Press, 2012

[3] Aggarwal, Ch. C., Recommender Systems, Springer, 2016

Note:

Further information:

https://courses.fit.cvut.cz/MI-ADM/

No time-table has been prepared for this course

The course is a part of the following study plans:

• Master branch Knowledge Engineering, in Czech, 2016-2017 (compulsory course of the specialization)
• Master branch Computer Security, in Czech, 2016-2019 (elective course)
• Master branch Computer Systems and Networks, in Czech, 2016-2019 (elective course)
• Master branch Design and Programming of Embedded Systems, in Czech, 2016-2019 (elective course)
• Master branch Web and Software Engineering, spec. Info. Systems and Management, in Czech, 2016-2019 (compulsory course of the branch)
• Master branch Web and Software Engineering, spec. Software Engineering, in Czech, 2016-2019 (elective course)
• Master branch Web and Software Engineering, spec. Web Engineering, in Czech, 2016-2019 (elective course)
• Master program Informatics, unspecified branch, in Czech, version 2016-2019 (VO)
• Master branch System Programming, spec. System Programming, in Czech, 2016-2019 (elective course)
• Master branch System Programming, spec. Computer Science, in Czech, 2016-2017 (elective course)
• Master branch Knowledge Engineering, in Czech, 2018-2019 (compulsory course of the specialization)