A groundbreaking work that transforms our understanding of the subject. This book has been acclaimed by critics and readers alike as a must-read masterpiece.
In this compelling and insightful work, the author delves deep into the subject matter, providing readers with a comprehensive understanding that is both accessible and profoundly enlightening.
Whether you're a novice looking to understand the basics or an expert seeking advanced insights, this book offers value at every level. The clear writing style and thoughtful organization make complex concepts easy to grasp.
based on 1,242 reviews
Technical Writer
"After spending considerable time with WebGPU and WGSL by Example: Fractals, Image Effects, Ray-Tracing, Procedural Geometry, 2D/3D, Particles, Simulations (Hardback), I'm impressed by how the author balances depth with accessibility. The first three chapters establish a strong foundation, while the middle sections develop the core concepts with numerous practical examples. The final section synthesizes these ideas in a way that feels both surprising and inevitable—a hallmark of excellent structuring."
Tech Journalist
"Fantastic read! Couldn't put it down. 5/5 stars!"
Cybersecurity Analyst
"Fantastic read! Couldn't put it down. 5/5 stars!"
Data Scientist
"What sets WebGPU and WGSL by Example: Fractals, Image Effects, Ray-Tracing, Procedural Geometry, 2D/3D, Particles, Simulations (Hardback) apart is its attention to nuance. Rather than presenting simplified models, the author embraces complexity while maintaining clarity. The case studies in chapters 5, 7, and 9 are particularly illuminating, demonstrating how the principles apply in varied contexts."
Software Engineer
"WebGPU and WGSL by Example: Fractals, Image Effects, Ray-Tracing, Procedural Geometry, 2D/3D, Particles, Simulations (Hardback) represents a significant contribution to the field. The author's meticulous research is evident throughout, with extensive references to both classical and contemporary works. The theoretical framework provides a robust foundation for the arguments presented, making this essential reading for scholars."
This is the kind of book that makes you want to open your IDE and start experimenting.
I keep this book on my desk—it’s my go-to reference for deep learning architecture design.
I've studied this book multiple times and still find fresh perspectives on system architecture.
A brilliant walkthrough of robotics kinematics—clear diagrams and solid math throughout.
I keep this book on my desk—it’s my go-to reference for deep learning architecture design.
This book should be required reading for anyone entering the field of quantum computing.
This book gave me the confidence to tackle my first real-world AI project from scratch.