by Aline Sindel, Katharina Breininger and Tobias Würfl
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
The exercises are implemented as python jupyter notebooks and were tested using Python 3.7 and 3.8.
For the exercises, you need to install the software python jupyter notebooks, which is included in the Anaconda distribution: https://www.anaconda.com/products/individual
Create a conda environment and install the required packages: conda install jupyter numpy unittest matplotlib scipy==1.5.2 pip install audioplayer
Link to a conda cheatsheet: https://docs.conda.io/projects/conda/en/latest/_downloads/843d9e0198f2a193a3484886fa28163c/conda-cheatsheet.pdf
The base source code is inside the main folder (where this README is located). For each exercise, one jupyter notebook will be provided in StudOn, which you have to download and store in the main folder. To start it, open a terminal (anaconda prompt), change to the main folder and then type 'jupyter notebook' to launch the Jupyter Notebook App. It will open in a new browser tab. Click on 'exercise1.ipynb' to start the first exercise.
More information about launching the jupyter notebook can be found at: https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/execute.html
All further steps are described in the jupyter notebook of the exercise. For each exercise, there are unittests embedded into the jupyter notebook such that you can check your implementation. After completing the exercise, answer the test questions in StudOn concerning the exercise.
If you have questions, while doing the exercises, use the forum to contact us or your fellow students.