184.702 Machine Learning
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2021W, VU, 3.0h, 4.5EC
TUWEL

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise
  • Format: Distance Learning

Learning outcomes

After successful completion of the course, students are able to...

- Formulate problems as specific Machine Learning tasks

- Understand of a range of machine learning algorithms and their characteristics

- Select the fitting methods for a specific learning goal

- Explain data preprocessing techniques

- Evaluate the methods for their suitability

Subject of course

Principles of Supervised and Unsupervised Machine Learning, including pre-processing and Data Preparation, as well as Evaluation of Learning Systems. Machine Learning models discussed may include e.g. Decision Tree Learning, Model Selection, Bayesian Networks, Regression techniques, Support Vector Machines, Deep Learning, Random Forests as well as ensemble methods.
 

Preliminary talk: 6.10.2021, via Zoom: https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09

Teaching methods

The course contains classroom lectures and exercises. Exercises include the application of machine learning techniques for various data sets and implementation of machine learning algorithms. The exercises are prepared at home and are presented/discussed during the exercise classes. 

Mode of examination

Immanent

Additional information

This course will be held completely in TUWEL - all lecture materials and news about the lecture will be made available there, and all questions regarding the course should be asked in the TUWEL forum *only*, not via TISS.


To get access to the TUWEL course, just apply to the group in TISS, and then follow the TUWEL link above

 

ECTS Breakdown:

13 classes (including prepration): 26 h

2 classes for presentations/discussions (including preparation): 8

Assignments: 46.5 h

exam: 32 h

---------------

total: 112.5 h

 

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed16:00 - 18:0006.10.2021 - 26.01.2022 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09 (LIVE)Lecture
Machine Learning - Single appointments
DayDateTimeLocationDescription
Wed06.10.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed13.10.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed20.10.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed27.10.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed03.11.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed10.11.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed17.11.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed24.11.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed01.12.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed15.12.202116:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed12.01.202216:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed19.01.202216:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture
Wed26.01.202216:00 - 18:00 https://tuwien.zoom.us/j/95543749056?pwd=NFFCdzYwcCtWN2x6d3RIV1RwVHZFZz09Lecture

Examination modalities

- Solving of exercises regarding experiments in machine learning, using a software toolkit of the student's choice (e.g. Python scikit-learn, Matlab, R, WEKA, ...)

- Written exam at the end of the semester

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Thu14:00 - 16:0021.10.2021 Zoomassessed04.10.2021 15:00 - 17.10.2021 23:59TISSExam (1st retake SS2021)
Wed - 08.12.2021assessed20.10.2021 00:00 - 30.11.2021 23:59TISSExam (2nd retake SS 2021)
Mon - 24.01.2022assessed13.12.2021 00:00 - 21.01.2022 23:59TISSExam (main date WS2021, 3rd& final retake SS 2021)

Course registration

Begin End Deregistration end
28.07.2021 00:00 10.10.2021 23:59 14.10.2021 23:59

Registration modalities

Acceptance to the course will be by the lecturers. Priority is given to

1.) Students that have this course as a compulsory or elective course (i.e. most computer science studies)

2.) ERASMUS students that have Machine Learning in their learning agreement.

3.) PhD students from the Faculty of Informatics

4.) Students that are currently in a bachelor programme of any of the studies mentioned in 1.), and are finishing their studies in the current semester. You will need to contact the lectureres (Rudolf Mayer, Nysret Musliu) and state your expected graduation, and which master programme you will continue

5.) If there are still free places afterwards, they will be assigned to master and PhD students from other faculties, and finally to all other students from other faculties. You need to contact the lecturers (Rudolf Mayer, Nysret Musliu) and state why the course is important for your studies. Note that the registration can be confirmed only when for the registration period ends.

Curricula

Literature

No lecture notes are available.

Previous knowledge

Self-Organising Systems (188.413) offers complementary topics in unsupervised data analysis. Information Retrieval (188.412) applies principles from Data Mining, Machine Learning

Problem Solving and Search in Artificial Intelligence (181.190) teaches some problem solving techniques that can be used in machine learning 

 

Accompanying courses

Continuative courses

Language

English