|19330101: Maschinelles Lernen für Data Science (VL/Ü)|
|The course provides an overview of machine learning methods and algorithms for different learning tasks, namely supervised, unsupervised and reinforcement learning. In the first part of the course, for each task the main algorithms and techniques will be covered including experimentation and evaluation aspects.|
|Dozent/in||Eirini Ntoutsi, Manuel Heurich|
|Zeit||27.09.2021 - 17.02.2022 |
Vorlesung: jeweils mittwochs (16-18 Uhr, Hörsaal Takustr. 9) und donnerstags (12-14 Uhr, Hörsaal Arnimallee 3) Übung: jeweils dienstags (12-14 Uhr und 14-16 Uhr), Takustr. 9, SR005.
|19331916: Forschungsseminar Artificial Intelligence and Machine Learning (Forschungsseminar)|
|The seminar takes place on a regular basis (weekly) with the aim to exchange information and ideas on AI and ML related topics. Many sessions take place in the form of a reading group, where we discuss the selected paper(s) on topics related to AI and ML. Everyone should read the paper(s) before the meeting to be able to actively participate in the discussions. Sometimes we have talks by ...|
|Zeit||21.10.2021 - 17.02.2022 |
Die Veranstaltung findet online per WebEx statt. Zugangsdaten siehe Whiteboard.
|19332311: Beyond machine learning: Exploring cognitive approaches to AI (Seminar)|
|Description Over the course of the last decade, machine learning has transformed not only AI as a field, but also many sectors of the economy. It is being successfully applied in predictive maintenance, smart grids, and vaccine development. Yet, ML has its limits. ML agents cannot be imaginative. They cannot perform well without a large quantity of high-quality data. And they cannot infer ...|
|Zeit||19.10.2021 - 15.02.2022 |
donnerstags 16-18 Uhr. Online per WebEx. Die Zugangsdaten werden im Whiteboard bekanntgegeben.