The WebGPU Sourcebook: High-Performance Graphics and Machine Learning in the Browser explains how to code web applications that access the client's graphics processor unit, or GPU. This makes it possible to render graphics in a browser at high speed and perform computationally-intensive tasks such as machine learning. By taking advantage of WebGPU, web developers can harness the same performance available to desktop developers. The first part of the book introduces WebGPU at a high level, without graphics theory or heavy math. The chapters in the second part are focused on graphical rendering and the rest of the book focuses on compute shaders. Because WebGPU enables web applications to access the GPU, it's quite possible that this final hurdle may be overcome. As I learned more about the subject, I became impressed by how simple the API was. Unlike OpenGL, WebGPU doesn't require vertex buffer objects and vertex array objects. Unlike Vulkan, WebGPU doesn't require lengthy swapchain and surface configuration. I'm thrilled to have the opportunity to present this fascinating subject, and I've split this book's content into three parts. The first part introduces WebGPU at a high level, without graphical rendering or computation. This part consists of Chapters 1 and 2, which presents the many JavaScript objects that applications need to create in order to access the GPU.