Avanceret machine learning | |
English | |
5 | |
MSc Offered as a single course Programme specific course (MSc), Business Analytics Programme specific course (MSc), Human-Centered Artificial Intelligence Programme specific course (MSc), Mathematical Modelling and Computation Technological specialization course (MSc), Business Analytics Technological specialization course (MSc), Human-Centered Artificial Intelligence Technological specialization course (MSc), Mathematical Modelling and Computation |
Spring F1B (Thurs 13-17)
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Campus Lyngby | |
Lectures with exercises, and periods of project work. | |
13 weeks | |
F1B | |
Written examination and reports
Reports and exam are equally weighted. The contribution of each student must be indicated in the reports. | |
Written exam: 2 hours | |
Written works of reference are permitted | |
7 step scale , external examiner | |
02450. 02456. 02476. 02477. 02405 , This course is an advanced course in machine learning. Students are expected to have passed most of the machine learning courses offered by DTU Compute before attending this course. At a minimum, students are expected to have passed 02450: Introduction to Machine Learning and Data Mining and 02456: Deep Learning. Students will benefit most from the course if they have also passed 02476: Machine learning operations, 02477: Bayesian machine learning, and 02405 Probability Theory. The course can be followed in parallel with 02477. |
Søren Hauberg , Ph. (+45) 4525 3899 ,
sohau@dtu.dk | |
Lars Kai Hansen , Lyngby Campus, Building 321, Ph.
(+45) 4525 3889 , lkai@dtu.dk Jes Frellsen , Lyngby Campus, Building 321, Ph. (+45) 4525 3923 , jefr@dtu.dk Mikkel N. Schmidt , Ph. (+45) 4525 5270 , mnsc@dtu.dk Morten Mørup , Ph. (+45) 4525 3900 , mmor@dtu.dk | |
01 Department of Applied Mathematics and Computer Science | |
At the Studyplanner | |
Please contact the teacher for information on whether this course gives the student the opportunity to prepare a project that may participate in DTU´s Study Conference on sustainability, climate technology, and the environment (GRØN DYST). More infor http://www.groendyst.dtu.dk/english |