Moses - Introduction to Machine Learning

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum WS 2019/20 - WiSe 2022/23.

Module / Version:
#50869 / #1

Validity:
WS 2019/20 - WiSe 2022/23

Default display language:
English

Module title:
Introduction to Machine Learning

Credits:
6

Responsible person:
Müller, Wolfgang

Grading:
benotet

Type of exam:
Mündliche Prüfung

Zugehörigkeit

Faculty:
Fakultät V

Institute:
Institut für Mechanik

Area of expertise:
35371100 FG Mechanik, insbes. Kontinuumsmechanik und Materialtheorie

Prüfungsausschuss:
Physikalische Ingenieurwissenschaft

Kontakt

Office:
MS 2

Contact person:
Rickert, Wilhelm

E-mail address:
wolfgang.h.mueller@tu-berlin.de

Website:

https://www.lkm.tu-berlin.de/menue/studium_und_lehre/

Learning Outcomes

Students learn the basics of how we teach machines to solve problems for us. Furthermore, the students learn how to improve their programming skills.

Content

Linear Regression, Logistic Regression, Regularization, Full-connected Neural Networks, Backpropagation algorithm, Convolutional Neural Networks, the Bayes Theorem, application to selected problems.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Introduction to Machine Learning	VL	3537 L 10382	k.A.	English	2

Workload and Credit Points

Introduction to Machine Learning (VL):

Workload description	Multiplier	Hours	Total
Attendance	15.0	2.0h	30.0h
Pre/post processing	15.0	4.0h	60.0h
			90.0h(~3 LP)

Course-independent workload:

Workload description	Multiplier	Hours	Total
Präsenzzeit	15.0	2.0h	30.0h
Vor-/Nachbereitung	15.0	4.0h	60.0h
			90.0h(~3 LP)

The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Lecture series

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Basic knowledge of linear algebra and confident programming is helpful

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Oral exam

Language

English

Duration/Extent

No information

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

none

Recommended literature
No recommended literature given

Assigned Degree Programs

This module is not used in any degree program.

Miscellaneous