Course details


Implementing Artificial Neural Networks with TensorFlow

L + S
WS 2020 Prof. Dr. Michael Franke
B.Sc modules:
CS-BWP-NI - Neuroinformatics
KOGW-WPM-NI - Neuroinformatics
M.Sc modules:
CC-MWP-NI - Neuroinformatics
CS-MWP-NI - Neuroinformatics
KOGW-MWPM-NIR - Major subject Neuroinformatics and Robotics

Prerequisites: Basic understanding of easy linear algebra concepts + experience with Python, NumPy and Jupyter Notebook. In this seminar, we will learn how to use the deep learning software library "TensorFlow" which is ideally suited and mostly used for the implementation of Artificial Neural Networks (ANNs). At the end of the course, you should be able to design different kinds of ANNs on a theoretical basis to solve real-world problems and you should be able to implement and train the ANN with the help of TensorFlow.