Workshop: Live Coding Machine Learning

Thursday 17th from 16h to 18h
Live Coding Machine Learning
Live Coding Machine Learning

This is a workshop related to the International Conference on Live Coding 2019.

This workshop is organised by Thor Magnusson, Chris Kiefer and TBC, all of whom are working on the MIMIC (Musically Intelligent Machines Interacting Creatively), implementing a live coding language for machine learning and machine listening. The project is a collaboration between Goldsmiths University, Durham University and the University of Sussex. Further info here: https://gtr.ukri.org/projects?ref=AH%2FR002657%2F1

Thor: http://www.sussex.ac.uk/profiles/164902

Chris: http://www.sussex.ac.uk/profiles/208667

This workshop introduces the role machine learning technologies can have in live coding performance and language design. The workshop is part of an early stage of the MIMIC research project, which explores how machine learning and machine listening can better be designed for user friendly and fast development cycles.

Participants will get familiar with selected machine learning classes in JavaScript, preparing them for further work in this exciting domain for musical investigation. The workshop will also include a brainstorming session and discussion on how we might develop a unique new live coding language for machine learning and machine listening. These fields represent complex computational techniques that can be difficult to understand by non-computer science creative coders. As a result of this workshop, we believe participants will gain a better understanding of what machine learning is, and we will have a better understanding of how such a live coding language might be designed.

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Organizador Actividad:
ICLC Local Committee
Personas relacionadas:
Patricia Domínguez Larrondo
Place:
Lab 1
Number of places:
0
30
Materials:
Laptop

Sessions of the activity

16:00 - 18:00
The activity is over
Laboratory:
AVLab
Tipo de actividad:
Taller de formación
Tags:
#avlab
Joint valuation:
Rango de edad:
0 - 100
Language:
English