Welcome to the course Musikinformatik of the Robert Schumann Hochschule Düsseldorf for SoSe 2021. The goal of this course is to introduce and learn common data analytic tools and machine learning algorithms for generating sounds. It will not just take a look at the practical aspects of this endeavor but also discuss philosophical and mathematical aspects of the discussed problems.
Within the course we will rely on the programming language Python - a high level scripting language - which became a per-se standard for data analytics and machine learning over the last years.
We will also rely on the sound platform SuperCollider for generating sounds.
Open for contributions!
If one comes across any mistake or has an suggestion for any improvements - do not hesitate to contribute! The source code for this course is open source and can be reviewed and improved by anybody. See :ref:`Contribute`.
.. toctree:: :maxdepth: 2 :caption: Course information docs/course-info/setup.rst docs/course-info/contribute.rst docs/bib.rst
.. toctree:: :maxdepth: 2 :caption: Basics docs/basics/math.rst 00_basics/sc_dimensions.ipynb docs/basics/python.rst 00_basics/py_dimensions.ipynb 00_basics/machine_learning.ipynb 00_basics/neural_networks.ipynb 00_basics/convolutions.ipynb 00_basics/autoencoders.ipynb 00_basics/lstm.ipynb 00_basics/osc_communication.ipynb 00_basics/compose.ipynb
.. toctree:: :maxdepth: 2 :caption: Using Python to synthesize sound 01_spect_resynth/canvas.ipynb 01_spect_resynth/02_spect.ipynb 01_spect_resynth/03_nmf.ipynb 01_spect_resynth/04_wavesets.ipynb
.. toctree:: :maxdepth: 2 :caption: Lesson 1 01_midi_drums/01_midi_drums.ipynb