Inhalt des Dokuments
Machine Learning I
The module "Machine Learning 1" is composed of the integreated lecture (6 LP) and one optional compulsory course (3 LP).
Teaching coordination and course inscription are done via the ISIS site of the integrated lecture . Detailed information on course formalities and accreditability are also summarized there. A description for external participants (Nebenhörer and Gasthörer) can be found below in the section on the online part of the course.
As thematical preparation, it is recommended to visit the MATLAB course or the mathematical foundations course which are also accreditable as optional compulsory course part and which (Cave!) take place in the weeks prior to the start of the lecture period.
||Thursday, 10:15 am - 11:45 am (starting 25.10.2012)
|room: MAR 0.016 |
|Exercise session ||Thursday, 12:15 pm - 13:45 pm
(starting 25.10.2012) |
|room: MAR 0.016 |
Dr. Klaus-Robert Müller  |
|office hours: by appointment
|Person of contact
||Dr. Franz Király  |
|office hours: by
In the lecture, introductory topics in the field of machine learning are presented.
After the lecture, the learnt methods are revisited and last week's exercises are explained in the exercise session.
Both lecture and exercise session are usually held in English.
The scheduled topics are:
|25.10.2012||Introduction to Machine
Learning and Statistics|
Estimation and Bayes Learning|
|10.01.2013||Learning Theory and Kernel
|24.01.2013||Kernel Ridge Regression
and Gaussian Processes|
Changes to the schedule will be announced through the ISIS mailing list.
Lecture slides and course materials are available at the ISIS on-line course .
The following are optional prerequisites which are helpful but not necessary for taking the course:
- Basic knowledge in linear algebra and calculus, as presented in the respective modules (German: Lineare Algebra, Analysis)
- Basic knowledge in probability theory, as presentid in the module stochastics (German: Elementare Stochastik)
- Basic programming knowledge, programming in MATLAB
The necessary prerequisites are in general presented and explained in the lecture or the exercise session.
For a brief review of the technical prerequisites, it is recommended to take the preparatory MATLAB and math foundation courses.
A successful participation in the integrated lecture and at least one optional compulsory course are mandatory for the registration for the machine learening 1 module exam.
The topics of the module exam are composed of the lecture topics and possibly topics treated in the optional compulsory exam. The module exam is a written exam which takes place at the end of the term and whose length is usually two hours. The first re-exam is a written exam, the second re-exam is an oral exam.
A successful participation in the integrated lecture consists of:
- having obtained 50% of the exercise points
- being allowed to participate in the integrated lecture "machine learning 1" without fulfilling any of the exclusion criteria described in the study regulations
The critera for a succesful participation in the optional compulsory courses differ by course.
For obtaining a certificate of participation, enrolment at the TU is neccessary in the form of a full enrolment, a Nebenhörerschaft or a Gasthörerschaft. For obtaining full accreditation, enrolment at the TU is neccessary in the form of a full enrolment or a Nebenhörerschaft.
More details on registration, exam modalities and accreditation can be found on the online part of the course.
Online course / ISIS
Link to the online course on ISIS 
Course organization and participation in the online course are carried out over the ISIS system  of the TU. For registration, a tubIT account is necessary. External participants who are enrolled at the TU (Nebenhörer and Gasthörer) can obtain an ISIS account at the tubIT  office. For this, it is necessary to apply for an account at the tubIT-Laden  with the Nebenhörer/Gasthörer enrolment certificate.
The discussion forums which are visible to all participants and the anonymous feedback possibilities can be used by all participants of the online part for asking questions and providing comments.
Exercises are a central part of the integrated lecture "machine learning 1". In the exercise sessions, questions about the lecture topics are answered and the necessary theoretical and practical foundations for the exercises are explained, when required the solutions to the exercises are presented.
Coordination of the exercises, including submission and grading of the solved exercises, are done via the ISIS system  of the TU. Each week, written and/or MATLAB programming problems are handed out.
Submission of the written exercises is also optionally possible in physical form.
MATLAB is installed on the systems administered by the IRB  and
can be accessed by executing the command
The computers of the IRB can only be accessed with an IRB accound which can be electronically requested  from the IRB by users of a tubIT account and external participants.