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Jayne :wales_flag:🇪🇺🏳️‍🌈 boosted

cultured nyc 🇺🇦

@culturednyc@mastodon.social · 3 days ago

If you're interested in using Python for music, whether that's algorithmic composition, computational music theory, or musicology, you've doubtless encountered music21. It's great, but can be a bit prickly. MIT has a great Open Courseware course with music21's creator, Michael Scott Asato Cuthbert, and it's really great! (Yes, that was the third time I said 'great' and that was the fourth.)

#python #algorithmicComposition #musicTheory #music21 #great #fifth

https://ocw.mit.edu/courses/21m-383-computational-music-theory-and-analysis-spring-2023/

MIT OpenCourseWare

Computational Music Theory and Analysis | Music and Theater Arts | MIT OpenCourseWare

This course presents major approaches to computational music theory and musicology in the symbolic (score-based) domain. It covers algorithms for music theory, encoding, corpus studies, musical search and similarity, feature extraction and machine learning, music generation, and computational music perception. Other topics include repertory access and computational bias. Programming assignments are in {{% resource_link "df43b258-7896-415a-a0f3-2ee18c498fa8" "Python" %}} using the MIT-created {{% resource_link "078ed66c-bf67-4c1b-adcd-caf5cc0c4c0e" "music21 toolkit." %}}

cultured nyc 🇺🇦

@culturednyc@mastodon.social · 3 days ago

If you're interested in using Python for music, whether that's algorithmic composition, computational music theory, or musicology, you've doubtless encountered music21. It's great, but can be a bit prickly. MIT has a great Open Courseware course with music21's creator, Michael Scott Asato Cuthbert, and it's really great! (Yes, that was the third time I said 'great' and that was the fourth.)

#python #algorithmicComposition #musicTheory #music21 #great #fifth

https://ocw.mit.edu/courses/21m-383-computational-music-theory-and-analysis-spring-2023/

MIT OpenCourseWare

Computational Music Theory and Analysis | Music and Theater Arts | MIT OpenCourseWare

This course presents major approaches to computational music theory and musicology in the symbolic (score-based) domain. It covers algorithms for music theory, encoding, corpus studies, musical search and similarity, feature extraction and machine learning, music generation, and computational music perception. Other topics include repertory access and computational bias. Programming assignments are in {{% resource_link "df43b258-7896-415a-a0f3-2ee18c498fa8" "Python" %}} using the MIT-created {{% resource_link "078ed66c-bf67-4c1b-adcd-caf5cc0c4c0e" "music21 toolkit." %}}

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