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Courses in winter term 2020 / Lab Course: Deep Learning

The lab allows students to gain practical knowledge and capabilities in the area of Deep Learning. This implementation-oriented course offers hands-on experience with current algorithms and approaches in Deep Learning and their application to real-world learning and decision-making tasks. This course will provide capabilities for students to reproduce experiments seen in papers and also how to model their discoveries. This course also aims to guide students in how to use Deep Learning tools and also to adopt healthy implementations practices. The methods being taught will change according to recent publications allowing students to participate in research in current topics. Methods will include:
Basic usage of Deep Learning Tools
Implementation of basic types of networks: CNN, RNN, and FCN.
Data Pre-Processing
Image Classification
Image Segmentation
Time Series Analysis
Reccomender Systems

Instructors: Rafael Rego Drumond
Time: Wed 14-18
Location: C 147
Begin: 28.10.2020
Assignment: MSc WI & IMIT & DA
Modul- Handbuch:MHB
Last Lecture: here