FluCoMa (https://www.flucoma.org/) is a toolkit for making music with machine listening and machine learning within Max, SuperCollider, & Pure Data. The toolkit offers audio decomposition tools to separate real-time and recorded audio into component elements, audio analysis tools to describe audio components as analytical and statistical representations, data analysis and machine learning algorithms for pattern detection and expressive corpus browsing, and audio morphing and hybridization algorithms for audio remixing, interpolating, and variation-making.

For more descriptive information about teaching FluCoMa, see FluCoMa for Pedagogues.

Special thanks to PA Tremblay, Owen Green, James Bradbury, Gerard Roma, Alex Harker, and Jacob Hart for all of their work on FluCoMa including many of these pedagogical materials.