VŠTE:SNS Machine Learning and Neural Ne - Course Information
SNS Machine Learning and Neural Network
Institute of Technology and Business in České Budějovicewinter 2020
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: z (credit).
- Teacher(s)
- doc. Ing. Vojtěch Stehel, MBA, PhD. (seminar tutor)
- Guaranteed by
- doc. Ing. Vojtěch Stehel, MBA, PhD.
Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice
Supplier department: Faculty of Technology – Rector – Institute of Technology and Business in České Budějovice - Timetable of Seminar Groups
- SNS/S01: Wed 11:25–12:55 D617, V. Stehel
- Prerequisites
- FORMA ( P )
Basics of working with Matlab, or willingness to learn them in the first weeks. - Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives supported by learning outcomes
- Students will learn the most common algorithms for machine learning. He is able to optimize these algorithms and apply them in practice.
- Learning outcomes
- The student knows commonly used algorithms for machine learning including basic neural networks. Students can practically use algorithms in their application. The student can also optimize the results. The student is able to understand the principle of machine learning, errors that can occur in coding and interpretation of results.
- Syllabus
- 1. Machine learning - introduction 2. Data acquisition and preparation 3. Regression and classification 4. Nearest Neighbor 5. Naive Bayes Classification 6. Discriminant Analysis 7. Support Vector Machines 8. Trees 9. Gaussian Process Regression 10. Improving Predictive Models 11. Neural network 12. Self-Organizing Maps and Feed-Forward Networks 13. Deep Learning
- Literature
- recommended literature
- Kvasnička, V. - Beňušková, L. - Pospíchal, J. - Farkaš, I. - Tiňo, P. - Kráľ, A.:Úvod do teórie neurónových sietí. IRIS, Bratislava 1997.
- Šíma, J. Generalized back propagation for interval training patterns, Neural Network World 2 (1992), 167-173.
- Šíma, J. - Neruda, J.: Teoretické otázky neuronových sítí. Matfyzpress, Praha 1996.
- Forms of Teaching
- Lecture
Seminar
Exercise
Excursion - language
Tutorial
Consultation
Teaching Block - tutorial - Teaching Methods
- Frontal Teaching
Group Teaching - Competition
Group Teaching - Cooperation
Group Teaching - Collaboration
Project Teaching
Brainstorming
Critical Thinking
Individual Work– Individual or Individualized Activity
Teaching Supported by Multimedia Technologies
- Student Workload
Activities Number of Hours of Study Workload Daily Study Combined Study Preparation for Seminars, Exercises, Tutorial 5 15 Preparation for the Final Test 3 25 Seminar work 18 Attendance on Seminars/Exercises/Tutorial/Excursion 26 12 Total: 52 52 - Assessment Methods and Assesment Rate
- Seminary Work 100 %
- Exam conditions
- 100 % seminar work
- Language of instruction
- Czech
- Enrolment Statistics (winter 2020, recent)
- Permalink: https://is.vstecb.cz/course/vste/winter2020/SNS