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=== Prerequisites === There are no formal entry requirements. However, we strongly recommend * the lecture ''Machine Learning 1'', * the course ''Python Programming for Machine Learning'' and * ideally, the ''Lab Course Machine Learning''. Students who do not have attended these lecture, should make sure they have the following skills: * '''Basic theory:''' Students should be fluent in probability theory, linear algebra and understand how and why mainstream learning algorithms work. * '''Some practical ML experience:''' Prior exposure to the practical application of ML algorithms is essential; students should know how to select hyperparameters and assess the performance of a trained predictor. * '''Python programming:''' All code that is to be handed in must be written in Python; students should be able to program in Python using the packages `numpy` and `scipy`. |
Project Machine Learning (Projekt Maschinelles Lernen)
General Information
First meeting |
Wednesday, October 16, 2019, 10:15am, Room TBA |
Responsible |
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Contact |
Jacob Kauffmann j.kauffmann@tu-berlin.de |
Language |
Englisch |
Credit |
M.Sc. Modul (Projekt), 9 LP (ECTS), PÄS |
Course Information |
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Enrollment open |
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Additional information is provided in a supplementary PDF
First Meeting
Our first meeting is October 16, 2019 at 10:15am.
Enrollment / Limited number of participants
The course has a a limit of 30 participants. If you intend to participate, please send an e-mail to j.kauffmann@tu-berlin.de as early as possible since we assign spots mostly on a first come / first serve basis. It is mandatory to attend the first meeting or e-mail the course organizer if this should not be possible. Otherwise we assume that you have no interest in the course anymore and give your spot to someone else.