Selected Topics of Artificial Intelligence

Organisation

Announcements

• First lesson in WS ²⁵⁄₂₆: 08.10.2025

Content

Currently the by far most prominent category of AI is Machine Learning, in particular Deep Learning. Deep Neural Networks have revolutionized many tasks of Computer Vision, Natural Language Processing, Data Mining, Time Series Prediction, Control and many others. Moreover, this type of AI has enabled new applications like automatic content generation, question answering etc. In order to build, train, evaluate and apply neural networks we usually apply Python frameworks like Pytorch or Tensorflow/Keras. This lecture introduces into the Python-based Deep Learning framework Pytorch. First some general concepts of Pytorch are described. After this, Deep Neural Networks for selected applications from the fields of Computer Vision, Natural Language Processing, Data Mining and Control are implemented in Pytorch.

Jupyterbook of this lecture

The following screenshot of the lectures Jupyterbook displays the content.

Video Lectures

Remark: It is important that all students of this lecture are aware of the fundamentals of Machine Learning as teached in the lecture Artificial Intelligence. As a refresher for this absolutely required knowledge, you may watch the videos listed below:

• Introduction to Machine Learning
• Basics of Neural Networks
• Basics of Deeplearning

Grading

At the end of the term student-groups have to implement a Deep Learning Project of their choice in Pytorch. This project and an oral exam will make up the final grade.