Alexandre DuBreuil Bücher

Explore the intersection of machine learning and music generation with a hands-on approach using Magenta. This resource delves into how ML, deep learning, and reinforcement learning contribute to creating music, guiding you in integrating these models into your existing production workflow. With practical examples and theoretical insights, you'll learn to generate percussion sequences, melodies in MIDI, and instrument sounds in raw audio. Key models such as RNNs, VAEs, and GANs are covered, enabling you to create and train your own models for advanced music generation. You'll also learn to prepare datasets tailored to specific styles and instruments, troubleshoot training issues, and synchronize Magenta with digital audio workstations (DAWs). Additionally, discover how to use Magenta.js for distributing music generation applications in the browser. By the end, you'll be equipped with the skills to harness ML models for music generation in your unique style. This resource is ideal for artists with a technical background and computer scientists with a passion for music, eager to build innovative music generation tools.