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Gene Kogan: Machine Learning for Artists


This workshop introduces the theory and application of machine learning for creative and artistic practice. It will focus on core algorithms used for parsing, visualizing, and discovering patterns in complex multimedia data, including images, sounds, and text. We will learn how to use neural networks to create real-time, cross-modal interactions for use in video and installation, as well as live music performance. We will also provide tools and code for clustering, visualizing, and searching through large collections of multimedia. 

Prior coding experience in a text-based (Python, Java, C++) or patch-based (Max/MSP) programming environment is helpful but not necessary.

 

TIMETABLE

Saturday 18th Feb

0930-1000 Tea and setup 

1000-1300 Workshop 

1300-1400 Lunch break

1400-1800 Workshop 


 Sunday 19th Feb

 0930-1000 Tea and setup 

 1000-1300 Workshop 

 1300-1400 Lunch break

 1400-1800 Workshop 

Tea and coffee will be provided. You can either bring your own lunch or there are various nearby cafes and shops to buy lunch on the day.

Course requirements: Please bring your own laptop

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GENE KOGAN

Gene Kogan is an artist and a programmer who is interested in generative systems, artificial intelligence, and software for creativity and self-expression. He is a collaborator within numerous open-source software projects, and leads workshops and demonstrations on topics at the intersection of code, art, and technology activism. Gene initiated and contributes to ml4a, a free book about machine learning for artists, activists, and citizen scientists. He regularly publishes video lectures, writings, and tutorials to facilitate a greater public understanding of the topic.