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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.

Python

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.

JavaScript

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.
MusicVAE
Creating palettes for blending and exploring musical loops and scores.
Learn more.
NSynth
Making music using new sounds generated with machine learning.
Learn more.

What's new?

Hip-Hop EP co-produced using Machine Learning
In this guest post, MJ Jacob discusses how he used Magenta models in the process of creating his new EP. Read the blog post.
Natya*ML
Through Natya*ML, I sought to showcase the beauty of Bharatanatyam in a way that’s easy and understandable. Read the blog post.
Maestro: An AI-guided vocal coach
We leveraged the Magenta.js library to create Maestro, an application that combines music theory with practical lessons for music enthusiasts. Read the blog post.
DearDiary.ai
Type some words—thoughts, feelings, poems, goals, stories, a to-do list—and you’ve created an original song. Read the blog post.
See more posts.