263-3210-00L  Deep Learning

SemesterAutumn Semester 2016
LecturersT. Hofmann
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 120.



Courses

NumberTitleHoursLecturers
263-3210-00 VDeep Learning2 hrs
Mon10:15-12:00IFW A 36 »
T. Hofmann
263-3210-00 UDeep Learning1 hrs
Mon13:15-14:00ML F 38 »
15:15-16:00CAB G 51 »
T. Hofmann

Catalogue data

AbstractDeep learning is an area within machine learning that deals with algorithms and models that automatically induce multi-level data representations.
ObjectiveIn recent years, deep learning and deep networks have significantly improved the state-of-the-art in many application domains such as computer vision, speech recognition, and natural language processing. This class will cover the fundamentals of deep learning and provide a rich set of hands-on tasks and practical projects to familiarize students with this emerging technology.
Prerequisites / NoticeThe participation in the course is subject to the following conditions:
1) The number of participants is limited to 120 students (MSc and PhDs).
2) Students must have taken the exam in Machine Learning (252-0535-00) or have acquired equivalent knowledge.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits4 credits
ExaminersT. Hofmann
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is only offered in the session after the course unit. Repetition only possible after re-enrolling.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationStudents are offered a project (40 hours) with bonus effect on the grade.
Grade = {exam, 0.7 exam + 0.3 project}
Written aidslimited aids (4 x A4 pages of notes)
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkInformation
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

Places120 at the most
Waiting listuntil 03.10.2016

Offered in

ProgrammeSectionType
Certificate of Advanced Studies in Computer ScienceFocus Courses and ElectivesWInformation
Computer Science MasterFocus Elective Courses Information SystemsWInformation
Computational Science and Engineering MasterElectivesWInformation