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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?

AI Song Contest: Human-AI Co-Creation in Songwriting
What are the challenges in using AI as a tool in songwriting? What are the design implications? Read the blog post.
Tone Transfer
Transform everyday sounds into musical instruments. Record and hear yourself as flutes, saxophones and more! Read the blog post.
Lo-Fi Player
A magical room where you can interact with music and have fun. Explore the possibilities by tinkering with the objects in the room. Read the blog post.
The Musician in the Machine
Guest blogger Dan Jeffries discusses how he and his team dug deep to find out if neural nets can compose Ambient music with the great masters of the art. Read the blog post.
See more posts.