Module 39-M-Inf-VML Advanced Machine Learning

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Explanation regarding the elements of the module

In some degree programmes, the module (partial) examination can also be "ungraded" at the student's discretion. A corresponding specification must be made before the module is taken; a subsequent change (graded - ungraded) is not possible. If the ungraded option is selected, it is not possible to use this module for a degree programme in which this module is taken into account in the overall grade calculation.

Advanced machine learning (exercise)

Reference no. Teaching staff Topic Type Dates My eKVV
392119 Ritter   Übungen zu Vertiefung Maschinelles Lernen Ü Fri 8-10 ON SITE & ONLINE in X-E0-236 [10.10.2022-03.02.2023] Hybridform 392119: Set in timetable
392128 Melnik   Tutorials "Applied Deep Learning" Course taught in English Ü Tue 8-10 (every two weeks) ON SITE & ONLINE in X-E0-216 [18.10.2022-03.02.2023] 392128: Set in timetable
392135 Ritter   Theory of Deep Neural Networks Course taught in English Ü Fri 10-12 (every two weeks) ON SITE & ONLINE in X-B2-101 [17.10.2022-03.02.2023] hybrid form 392135: Set in timetable

Advanced machine learning (lecture)

Reference no. Teaching staff Topic Type Dates My eKVV
392117 Ritter   Vertiefung Maschinelles Lernen V Thu 08-10 ON SITE & ONLINE in X-E0-200 [10.10.2022-03.02.2023] Hybridform 392117: Set in timetable
392127 Melnik   Applied Deep Learning Course taught in English V Mon 8-10 ON SITE & ONLINE in X-E0-216 [10.10.2022-03.02.2023] 392127: Set in timetable
392132 Ritter   Theory of Deep Neural Networks Course taught in English V Thu 14-16 ON SITE & ONLINE in X-E0-205 [10.10.2022-03.02.2023] hybrid form 392132: Set in timetable

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Uses