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You're reading from Hands-On Music Generation with Magenta Explore the role of deep learning in music generation and assisted music composition

Product type Paperback

Published in Jan 2020

Publisher

ISBN-13 9781838824419

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

Magenta

Concepts

Deep Learning

Author (1):

Alexandre DuBreuil

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Table of Contents (16) Chapters

Preface

1. Section 1: Introduction to Artwork Generation

2. Introduction to Magenta and Generative Art FREE CHAPTER

3. Section 2: Music Generation with Machine Learning

4. Generating Drum Sequences with the Drums RNN

5. Generating Polyphonic Melodies

6. Latent Space Interpolation with MusicVAE

7. Audio Generation with NSynth and GANSynth

8. Section 3: Training, Learning, and Generating a Specific Style

9. Data Preparation for Training

10. Training Magenta Models

11. Section 4: Making Your Models Interact with Other Applications

12. Magenta in the Browser with Magenta.js

13. Making Magenta Interact with Music Applications

14. Assessments

15. Other Books You May Enjoy

Leave a review - let other readers know what you think

Learn Live (Ableton Live): Amazing tutorials on Ableton Live, which are far the best tutorials available on music production in general, with advanced content on many topics that can be used in many DAWs (www.ableton.com/en/live/learn-live/)
Session View (Ableton Live): More information on Ableton Live's Session View which is a useful view for using Magenta Studio (www.ableton.com/en/manual/session-view/)
Community Learning (Bitwig): Good tutorials for Bitwig (www.bitwig.com/en/community/learning.html)
Tutorials (Reason): Tutorials for Reason in the form of blog posts (www.reasonstudios.com/blog/category/tutorials)
Getting Started With SC (SuperCollider): The best way to get into SuperCollider and its programming language, sclang—the examples are also bundled with the software when downloaded (doc.sccode.org/Tutorials/Getting-Started/00-Getting-Started...

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Authors (1)

DuBreuil

Alexandre DuBreuil is a software engineer and generative music artist. Through collaborations with bands and artists, he has worked on many generative art projects, such as generative video systems for music bands in concerts that create visuals based on the underlying musical structure, a generative drawing software that creates new content based on a previous artist's work, and generative music exhibits in which the generation is based on real-time events and data. Machine learning has a central role in his music generation projects, and Alexandre has been using Magenta since its release for inspiration, music production, and as the cornerstone for making autonomous music generation systems that create endless soundscapes.

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