Music AI Tutorial

The Music AI Tutorial is a collection of cloud-based, interactive tutorials that teach topics in Music, Artificial Intelligence, and Computer Science. The tutorial takes a historical approach. My intention is to give cultural, technical, and aesthetic context to contemporary approaches to Music AI.

The tutorial is intended to be viewed using Google Colaboratory, a cloud-based Jupyter Notebook environment, which allows you to edit and run code in the browser. However, you can also view a static render of the tutorial by following the links below (recommended if you don’t plan on editing code).

The Music AI Tutorial (static version)

1. Intro to Python for Music
   1. Hello Python
   2. Hello Music
2. Coding the Illiac Suite
   1. Programming Logic
   2. Generate and Test
   3. Coding the Illiac
3. Parametric Models
   1. Anna’s Music Box
   2. Functions
4. Transitions and States
   1. Probability and DJEN
   2. Markov Chains
   3. Higher Order Markov Chains
   4. Learning Billie Jean
5. Genetic Algorithms
   1. Hello Genetic Algorithm
   2. Evolved FM
6. Swarms and Distributed Models
   1. Boids Music
   2. Cellular Automata
7. Machine Listening
   1. The Speaking Piano
   2. Timbre / Remix
   3. Audio -> MIDI Transcription
   4. Similarity and the Infinite Jukebox
8. Neural Networks
   1. Single Layer Perceptron
   2. Multilayer Perceptron
   3. Generating Sequences
   4. Semantic Spaces

Music AI Tutorial on Google Colaboratory (interactive version)

Accompanying github code repository MAI: Music and Artificial Intelligence.

Note: This is an incomplete draft. The Music AI Tutorial is currently a work in progress. Sections without links are either in-progress drafts or are waiting for me to figure out how best to port Processing + Audio to the web using web audio.