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

Difficulty level:¬†Beginner 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. In this workshop we will demystify the Markov... Read More

Algorithmic Composition in Max: Bringing Order to Chaos

Learn to construct music-generating algorithms in Max, to compose semi-autonomously or supplement your compositional practice. Level: Intermediate¬† Composing with¬†randomness For centuries, musicians have incorporated chance-based elements into their compositions, first through coin flips and dice rolls and more recently through computer software. Today, building music-oriented algorithmic systems is easier than ever with Max. What you will learn In... Read More