Max Packages

Data Knot

Developed by long-time Max contributor Rodrigo Costanzo (co-author of the karma package), Data Knot builds on the power of FluCoMa to provide a set practical and inspiring machine-learning tools purpose-built for performing musicians.

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Machine Learning Packages

Data Knot

by Rodrigo Constanzo

Machine Learning tools for low latency real-time performance

CataRT-MuBu

by IRCAM & ISMM Team

CataRT-MuBu is a collection of Max patches for corpus-based concatenative synthesis, audio mosaicing, descriptor analysis, transcription, and composition (MuBu package required).

Fluid Corpus Manipulation instigates new musical ways of exploiting ever-growing banks of sound and gestures within the digital composition process -- a DSP and machine learning toolset.

ml.lib

by IRL Labs

A library of machine learning externals and feature extraction externals for Max and Pure Data. ml-lib is primarily based on the Gesture Recognition Toolkit by Nick Gillian

MuBu For Max

by ISMM Team & IRCAM

A toolbox for Multimodal Analysis of Sound and Motion, Interactive Sound Synthesis and Machine Learning.

ml.star

by Benjamin D. Smith

Unsupervised machine learning algorithms to support on-line learning, and real-time interactive music and video, aimed at the computer artist and musician.

cv.jit

by Jean-Marc Pelletier

A collection of max/msp/jitter externals, abstractions and help files for computer vision applications originally authored by Jean-Marc Pelletier.

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