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Deep Learning Lab

Description

This course offers an opportunity to acquire practical experience in using TensorFlow to implement feedforward and recurrent neural networks (e.g., long short-term memory networks). Such networks currently achieve state-of-the-art results in many exciting tasks, such as object recognition, speech recognition, language translation, and learning to play games from experience. TensorFlow is an open source library developed by Google, and currently is perhaps the most popular choice among researchers and practitioners. The course will consist in practical assignments and a final course project, possibly proposed by the student.

People

 

Rauber P.

Course director

Schlag I.

Assistant

Additional information

Semester
Fall
Academic year
2017-2018
ECTS
3
Education
Master of Science in Artificial Intelligence, Core course, Lecture, 1st year

PhD programme of the Faculty of Informatics, Elective course, Laboratory, 1st, 2nd and 3rd year (2 ECTS)