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Make Music and Art
Using Machine Learning

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What is Magenta?

An open source research project exploring the role of machine learning as a tool in the creative process.


Magenta is distributed as an open source Python library, powered by TensorFlow. This library includes utilities for manipulating source data (primarily music and images), using this data to train machine learning models, and finally generating new content from these models.


Magenta.js is an open source JavaScript API for using the pre-trained Magenta models in the browser. It is built with TensorFlow.js, which allows for fast, GPU-accelerated inference. If you're interested in seeing how Magenta models have been used in existing applications or want to build your own, this is probably the place to start!

Featured projects

Magenta Studio (beta)
Magenta Studio is a collection of music plugins built on Magenta’s open source tools and models.
Learn more.
Onsets and Frames
Transcribing piano with a neural network.
Learn more.
Creating palettes for blending and exploring musical loops and scores.
Learn more.
Making music using new sounds generated with machine learning.
Learn more.

What's new?

Magenta + Deeplocal +
The Flaming Lips = Fruit Genie
Creating an AI-assisted performance as part of the headline concert at I/O 2019. Read the blog post.
GrooVAE: Generating and Controlling Expressive Drum Performances
GrooVAE models expressive drumming. Read the blog post.
WiMIR Workshop 2018
Building Bridges at WiMIR 2018. Read the blog post.
Coconet: the ML model behind today’s Bach Doodle
We present Coconet, the ML model behind today's Bach Doodle. It is a versatile model of counterpoint that can infill arbitrary missing parts by rewriting the musical score multiple times to improve its internal consistency. Read the blog post.