Course template / hosted architecture draft

An Introduction to Markov Chains: Machine Learning in Max

Markov chains are mathematical models that have existed in various forms since the 19th century, which have been used to aid statistical modelling in many real-world contexts, from economics to […]

Level

Level 1

Duration

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Format

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Course overview

Markov chains are mathematical models that have existed in various forms since the 19th century, which have been used to aid statistical modelling in many real-world contexts, from economics to cruise control in cars. Composers have also found musical uses for Markov Chains, although the implied mathematical knowledge needed to implement them often appears daunting.

Who is this course for?

• This course is for musicians interested in getting creative with their compositions by using Markov Chains.

Requirements

• You should have a basic understanding of the Max workflow and different data types.
• Knowledge of MIDI format and routing to DAWs (Ableton, Logic etc) would be a plus, although Max instruments will be provided.
• No prior knowledge of advanced mathematical or machine learning concepts are necessary, the focus will be on musical application.

Course content

Session 1

An Introduction to Markov Chains: Machine Learning in Max/MSP - LIVE session

Part 1 - A Non-Musical Probability Example · Part 2 - Building a Basic Markov Chain from Scratch · Part 3 - Implementing ml.markov and Using a Longer Melody to Explore Markov Chain Order