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The Deep Learning Lab is a course at the Institute for Communications Technology that is primarily aiming to impart knowledge for students in the fields of machine learning and pattern recognition through practical applications. Students learn to implement and configure machine learning algorithms by completing the course. The lab is closely related to the pattern recognition lecture where algorithms and theory are taught. The Deep Learning Lab is intended as a hub for students, PhD students, industry and cooperations to facilitate knowledge exchange and pooling of common interests. The project is funded by the Federal Ministry of Education and Research.
The Machine Learning Computer Lab
The Deep Learning Lab consists of three parts:
First, the students work themselves through an introduction to the Python programming language and all required libraries for the later experiments to obtain basic knowledge.
Second, the students will apply certain machine learning algorithms to artificial and real-world problems to get a feeling for the training parameters, processes, different toolkits and cluster software.
Third, - in the so-called Machine Learning Challenge - students are required to use their obtained knowledge in order to develop a machine learning system in a competition with the other participating groups. Therefore, the students will be ideally provided with real data which might stem from real-world/industry applications.
Student teams working on the AI tasks of the Deep Learning Lab
The Machine Learning Challenge
The Deep Learning Lab finishes with a closing event in summer each year. Each student team presents its solution for the Machine Learning Challenge. The three best teams receive a certificate showing their rank in the challenge. The event allows representatives from industry acting as a sponsor to present their company and to get into contact with young AII experts, as about 50 Master and Ph.D. students participate in the closing event each year. The award ceremony is usually accompanied by a sponsored buffet with food from the grill and cold beverages.
Picture of the closing event at the end of a Deep Learning Lab with presentations from each group, sponsors, and if applicable also a live demonstration of the winning system.
How to contribute?
Industry may want to take part as a partner by
- contributing a machine learning challenge and task from its own real-world data
- providing internships to our students
- cooperating with us in a research project on AI and machine learning
- becoming a sponsor for the closing event of the Deep Learning Lab, presenting their company and get into contact with young AI experts
Students who are interested in machine learning or deep learning are encouraged to visit the course in the summer semester to obtain practical experience with toolkits, databases and algorithms. Moreover, potential future employers can be met. Further information can be found on the lab homepage.
Andreas Bär: email@example.com
Prof. Dr.-Ing. Tim Fingscheidt: firstname.lastname@example.org
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