We Move Session: Sara Adkins - Machine Learning and Composition hero

Creative Coding

We Move Session: Sara Adkins - Machine Learning and Composition

Together with Sara Adkins, this session demystified the buzzword "machine learning", exploring in an accessible way what Machine Learning can achieve in the field of creativity. Geared towards…

Level

Beginner

Duration

Self-paced

Format

Recorded meetup

Added

07/05/2022

Course overview

Together with Sara Adkins, this session demystified the buzzword "machine learning", exploring in an accessible way what Machine Learning can achieve in the field of creativity. Geared towards beginners in ML/AI/coding.

Topics covered: what machine learning is and how applying it to creative fields differs from traditional use / applications in music creation including melody and lyric generation, harmonisation, timbre transfer, and improvisation partners / tools available to musicians that don't require coding / pros and cons of incorporating ML into your creative process.

Course content

URL Event

1 resource, 1 lesson

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Instructors

Sara Adkins

Sara Adkins

Instructor

Sara Adkins is a music technologist, guitarist and software engineer passionate about promoting the use of machine learning and AI in the creative arts. She is a Fulbright grant recipient currently pursuing her Master of Science in Sound and Music Computing at Queen Mary University of London. Prior to moving to London she spent three years in Boston, working as a machine learning engineer at Bose and performing as a freelance classical guitarist. Sara’s senior capstone project, “Creating with the Machine,” was a set of compositions combining algorithmic and traditional methods of composition into live performances to explore how interactive generative algorithms can influence creativity in musical improvisation. “Creating with the Machine” was premiered by the Carnegie Mellon Exploded Ensemble in the spring of 2018, and was awarded the Henry Armero Memorial Award for Inclusive Creativity. Sara also presented the project at the 2019 Hackaday Superconference in LA.

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