Hands-On Music Generation with Magenta
The place of machine learning in art is growing at a rapid pace because of recent advancements in the field. Magenta is at the forefront of that innovation. This book provides a hands-on approach to machine learning models for music generation and demonstrates how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation
Offered by
Difficulty Level
Intermediate
Completion Time
12h
Language
English
About Book
Who Is This Book For?
This book is for technically inclined artists and musically inclined computer scientists. Readers who want to get hands-on with building generative music applications that use deep learning will also find this book useful. Although prior musical or technical competence is not required, basic knowledge of the Python programming language is assumed.
Hands-On Music Generation with Magenta
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 12h total length
Introduction on Magenta and generative art
Generating drum sequences with DrumsRNN
Generating polyphonic melodies
Score interpolation with MusicVAE
Audio generation with GANSynth
Data preparation and pipelines
Training an existing model on a specific style
Magenta in the browser with Magenta.js
Making Magenta interact with music applications
Related Resources
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