Introduction to WebNN API in 20 Minutes - Coffee Book Series (Paperback)

Introduction to WebNN API in 20 Minutes - Coffee Book Series (Paperback)

Various Authors January 22, 2025 Books, Computers & Technology, Computer Science, AI & Machine Learning, Neural Networks 979-8307908037
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About This Book

The web is evolving - and so is your web browser - your web browser is full of tools and resources that enhance your online experience, streamline your tasks, and ensure your security and privacy. One specific tool is the WebNN API, which provides access to neural network hardware acceleration to optimize performance for machine learning applications in the browser. The web is evolving, and so is your web browser; a treasure trove of tools and resources that enhance your journey through the online digital realm. Amidst this ever-growing machine learning landscape, one recent addition that shines brightly is the WebNN API. This specific API opens the door to online neural network hardware acceleration, offering seamless performance for machine learning applications, all within the confines of your browser (an open-standard that's part of the web to help - integrated into modern browsers so you don't require any external libraries).

Whether you're a beginner looking to learn the basics or an experienced professional seeking advanced knowledge, this book has something valuable to offer.

Key Features

  • Comprehensive coverage of Books concepts
  • Practical examples and real-world applications
  • Step-by-step tutorials and exercises
  • Written by industry experts
  • Companion website with additional resources

Book Statistics

Rating: 4.6
Reviews: 323
Pages: 400
Language: English
Sales Rank: #8379
Popularity: 92%

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Customer Reviews

Drew Garcia
Drew Garcia
Knowledge Manager at AI Horizons
Alright, this book? Totally worth it—especially if you’re into machine learning. Cool. The writer doesn’t overdo it—just solid points and good flow. Good one to keep around when you want something casual.
Parker Lewis
Parker Lewis
AI Ethicist at NextGen Systems
From a theoretical perspective on machine learning, this book offers Meticulously researched. An essential reference for serious scholars in the discipline. Key themes are examined with clarity and depth. Methodology is sound and consistently applied. The author demonstrates a profound understanding of the subject matter. This work bridges a critical gap in the existing literature. It deserves a prominent place in academic libraries.
Alex Martinez
Alex Martinez
IT Consultant at Amazon
Hey there! Just finished reading this gem about machine learning - Delightful. It somehow made me laugh and think at the same time. The tone was super inviting without dumbing things down. I loved how it mixed serious insight with friendly storytelling. Each chapter felt like chatting with a really smart friend. Give it a try—you might just love it too!
See All Reviews (228)

Community Discussions

Avery Hernandez
Avery Hernandez
June 21, 2025
This book is a must-read! I especially loved the part about the practical examples.
Reply
Quinn Walker
Quinn Walker
June 29, 2025
This book is brilliant! I especially loved the part about the clear explanations.
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Jamie Jones
Jamie Jones
June 28, 2025
This book is a must-read! I especially loved the part about the real-world applications.
Reply
Rowan Davis
Rowan Davis
July 8, 2025
This book is fantastic! I especially loved the part about the clear explanations.
Reply
Finley Wright
Finley Wright
June 20, 2025
This book is a must-read! I especially loved the part about the author's insights.
Reply
Elliot Roberts
Elliot Roberts
June 20, 2025
This book is fantastic! I especially loved the part about the author's insights.
Reply

Get Your Copy Today

Introduction to WebNN API in 20 Minutes - Coffee Book Series (Paperback)
4.0 (655 reviews)
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Book Details

  • Publisher: Independently published
  • Publication Date: January 22, 2025
  • Language: English
  • ISBN-10: 979-830790
  • ISBN-13: 979-8307908037
  • Pages: 716
  • Dimensions: 6 x 4.1 x 9.3 inches
  • Weight: 1.2 pounds

Keywords

machine learning