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Unsupervised Machine Learning via FluCoMa In Max

Taught by: Ted Moore

Sunday 29th January 4pm UK

The Fluid Corpus Manipulation project (FluCoMa) provides novel machine learning tools for use in the digital composition process. Unsupervised Machine Learning refers to algorithms and strategies used to find patterns in data that might not be known ahead of time. After using FluCoMa objects to analyze audio, unsupervised learning algorithms can help automatically find sounds that are similar or different, plot complex analyses in a navigable two-dimensional space, or help organize sound slices for interfacing with a controller. This gives a vast array of creative possibilities for composition, sound design and performance. In this workshop, Ted Moore from the FluCoMa project will guide you through an exploration of some of the creative possibilities available via Unsupervised Learning with the FluCoMa Max Package. Basic experience of FluCoMa is advised before joining this workshop. For example, it is strongly recommended that you have taken the free on-demand workshop Using Machine Learning Creatively via FluCoMa In Max.


Starts on: 29/01/2023 16:00 London time

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What you'll learn

  • Find patterns in unorganized or unknown data
  • Plot data in 2 dimensional space (or other dimensions) by adjusting object parameters
  • Cluster sound slices to identify sounds that are similar and different from others
  • Gridify data points for interfacing with controllers

Course content

  • Open the course in Zoom to access all the features
  • Patches and Slides
Membership plan: Going Deeper | Topic: Sound Design ...
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Buy this single course:

£ 30

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  • A computer and internet connection
  • A web cam and mic
  • A Zoom account
  • Access to a copy of Max 8 (i.e. trial or full license)
  • Install of the free FluCoMa Max package

Who is this course for

  • Sound designers looking to implement unsupervised machine learning tools via FluCoMa in Max
  • Musicians looking to explore the creative possibilities offered with unsupervised machine learning tools via FluCoMa in Max

Useful links

About the workshop leader

Ted Moore (he / him) is a composer, improviser, and intermedia artist. He holds a PhD in Music Composition from the University of Chicago and recently served as a Research Fellow in Creative Coding at the University of Huddersfield, investigating the creative affordances of machine learning and data science algorithms as part of the FluCoMa project.‚Äč His work focuses on fusing the sonic, visual, physical, and acoustic aspects of performance and sound, often through the integration of technology.