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Learning TensorFlow.js: Powerful Machine Learning in JavaScript 1st Edition
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Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde (Google Developer Expert in machine learning and the web) provides a hands-on end-to-end approach to TensorFlow.js fundamentals for a broad technical audience that includes data scientists, engineers, web developers, students, and researchers.
You'll begin by working through some basic examples in TensorFlow.js before diving deeper into neural network architectures, DataFrames, TensorFlow Hub, model conversion, transfer learning, and more. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems with TensorFlow.js.
- Explore tensors, the most fundamental structure of machine learning
- Convert data into tensors and back with a real-world example
- Combine AI with the web using TensorFlow.js
- Use resources to convert, train, and manage machine learning data
- Build and train your own training models from scratch
- ISBN-101492090794
- ISBN-13978-1492090793
- Edition1st
- PublisherO'Reilly Media
- Publication dateJune 15, 2021
- LanguageEnglish
- Dimensions7 x 0.75 x 9.25 inches
- Print length338 pages
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O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.
Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.
From the Publisher
From the Preface
Why TensorFlow.js?
TensorFlow is one of the most popular machine learning frameworks on the market. It’s supported by Google’s top minds and is responsible for powering many of the world’s most influential companies. TensorFlow.js is the indomitable JavaScript framework of TensorFlow and is better than all the competitors. In short, if you want the power of a framework in JavaScript, there’s only one choice that can do it all.
Who Should Read This Book?
Two primary demographics will enjoy and benefit from the contents of this book:
The JavaScript developer: If you’re familiar with JavaScript, but you’ve never touched machine learning before, this book will be your guide. It leans into the framework to keep you active in pragmatic and exciting creations. You’ll comprehend the basics of machine learning with hands-on experience through the construction of all kinds of projects. While we won’t shy away from math or deeper concepts, we also won’t overly complicate the experience with them. Read this book if you’re building websites in JavaScript and want to gain a new superpower.
The AI specialist: If you’re familiar with TensorFlow or even the fundamental principles of linear algebra, this book will supply you with countless examples of how to bring your skills to JavaScript. Here, you’ll find various core concepts illustrated, displayed, and portrayed in the TensorFlow.js framework. This will allow you to apply your vast knowledge to a medium that can exist efficiently on edge devices like client browsers or the Internet of Things (IoT). Read this book and learn how to bring your creations to countless devices with rich interactive experiences.
This book requires a moderate amount of comfort in reading and understanding modern JavaScript.
Editorial Reviews
From the Author
Be sure to share your creations, tag your work with the #MadeWithTFJS tag, and feel free to reach out to me to share your story. I'm excited and honored to be your guide.
From the Back Cover
"Learning TensorFlow.js enables you to take your first steps with TensorFlow.js, allowing any JavaScript developer to gain superpowers in their next web application and beyond" - Jason Mayes (Senior Developer Relations Engineer for TensorFlow.js, Google)
"Gant's ability to navigate explaining complexities of machine learning while avoiding the pitfalls of complicated mathematics is uncanny, and you'd be hard-pressed to find a better introduction to data science using JavaScript" - Lee Warrick (Full Stack JavaScript Developer)
About the Author
Product details
- Publisher : O'Reilly Media
- Publication date : June 15, 2021
- Edition : 1st
- Language : English
- Print length : 338 pages
- ISBN-10 : 1492090794
- ISBN-13 : 978-1492090793
- Item Weight : 2.31 pounds
- Dimensions : 7 x 0.75 x 9.25 inches
- Best Sellers Rank: #1,752,988 in Books (See Top 100 in Books)
- #291 in Java Programming
- #340 in JavaScript Programming (Books)
- #564 in Artificial Intelligence (Books)
- Customer Reviews:
About the author

Like the many algorithms he’s written over the past 20+ years, Gant Laborde
voraciously consumes vast quantities of data and outputs solutions. In his
early days, Gant created a website that became one of the top 100,000
websites worldwide. Now he’s Chief Innovation Officer and co-owner of
Infinite Red, an industry-leading web and app development company. Besides
managing an all-star roster of talent located across the globe, Gant is also
a published author, adjunct professor, volunteer mentor, and speaker at
conferences worldwide.
A personable mad scientist, Gant is a consummate explorer who loves
explaining and charting the things he discovers. From learning about AI and
teaching computers to do things he could never do on his own, to exploring
the topography of New Orleans with its masked balls and secret rooms, Gant
lives to find the next amazing, undiscovered thing. This approach to life
makes him an avid and formidable problem solver.
Whether a given question involves technology, processes, and/or people, Gant
approaches each problem with curiosity and enthusiasm. He’s a motivated
self-educator who thrives when passing along what he’s learned to others.
(That might explain why he goes on so many podcasts, but it doesn’t explain
why people keep sending him Nicolas Cage memes. It is a mystery. 👻) Gant is
also a lifelong advocate for open source.
A proud New Orleans native, Gant credits his city’s indomitable spirit as
the inspiration for his drive and ability to persevere through any obstacle.
“New Orleans doesn’t know how to quit,” Gant says. “That’s why I love it.”
Gant mentors at his local Toastmasters Club and channels his competitive
spirit into local dodgeball games, Rocket League, and Beat Saber (wanna
play?). Most importantly, he’s the proud father to his adorable daughter
Mila!
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This is a must read for anyone wanting to train their own network through machine deep learning
Top reviews from the United States
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- Reviewed in the United States on June 4, 2021Format: PaperbackVerified PurchaseLearning TensorFlow.js is an excellent resource to break the subject down to the fundamentals; and then it takes the reader's hand and leads him/her up to the complexities of this particular deep learning software.
In particular, I enjoyed the author's explanation of tensors. Note: the foreground of the book's photo that I have attached: I donated my chess board as an image tensor.
The reason that I read this book from cover to cover is because I truly believe that AI learning is going to be the next internet. In this book the author taught me to use Google's TensorFlow.js to maximize the return on any mathematical operation.
5.0 out of 5 starsLearning TensorFlow.js is an excellent resource to break the subject down to the fundamentals; and then it takes the reader's hand and leads him/her up to the complexities of this particular deep learning software.This is a must read for anyone wanting to train their own network through machine deep learning
Reviewed in the United States on June 4, 2021
In particular, I enjoyed the author's explanation of tensors. Note: the foreground of the book's photo that I have attached: I donated my chess board as an image tensor.
The reason that I read this book from cover to cover is because I truly believe that AI learning is going to be the next internet. In this book the author taught me to use Google's TensorFlow.js to maximize the return on any mathematical operation.
Images in this review
- Reviewed in the United States on August 2, 2021Format: PaperbackVerified PurchaseIf you want to know how to use JavaScript to manipulate data to form a model for a learning algorithm this book will get you started down that path. By learning TensorFlow.jd you will become one of the few JavaScript developers out there that possess a skill that is rapidly growing in demand. This book is your stepping stone.
- Reviewed in the United States on June 3, 2021Format: Paperback[Please note: I wrote the Foreword for this book]
Gant has done something special with this book. In just 300 pages, he takes you end-to-end, in-depth through everything you need to know from an introduction to AI, understanding tensors, using them in the browser, deploying them, and more.
It ends with a capstone project (what a great idea, I might have to steal it for my next book!), where you can use Machine Learning to convert an image into a set of dice, like the attached picture.
How much fun is that?
I love this book because it is for a different audience than the traditional ML one. It starts with a great introduction to AI and then tells you about TensorFlow.js and how you can use it to build Machine Learning apps. Then, the mystery of Tensors is cracked open, and Gant leads you through some detailed examples of how you can convert images into Tensors for training and inference.
It guides you through the three main ways to get a working model.
First, you can find an existing model from TensorFlow Hub, and in Chapter 5, Gant leads you through using the inception model in JavaScript. Inception isn’t any toy model, though – it is a Convolutional Neural Network designed for image analysis and object detection. It’s not that long ago that it was state-of-the-art in research. And now it’s available in JavaScript!
Or, you can create your model from scratch, and Gant takes you through the code for defining layers, with deep neural networks to help predict numeric data (such as the famous titanic dataset) or Convolutional Neural networks for image classification.
Finally, there’s Transfer Learning, which could be the most exciting method for most developers, where you have a hybrid of both of the previous methods. You can stand on the shoulders of giants by using parts of an existing model, like Inception, but catered for your own needs.
When I started my Machine Learning journey, one frustration I had was that there was lots of material for creating models but relatively little for using them. The tutorial would end with a validation set showing how accurate the model was, and then it would move on to the next thing! I am delighted to say that this book does not fall into that pattern! So, if you want to build a browser-based app that uses a model, you’ll get lots of code showing you how!
For example, Chapter 6 shows you how to use the webcam in the browser, capturing frames and passing them to a model for classification. Chapter 10 shows you how to create a basic sketchpad for drawing images that a model can interpret.
Whether you’re an experienced Machine Learning expert, looking to see how to apply JavaScript to help solve your problems, or a JavaScript developer who wants to enter the wonderful world of ML, this book is for you.
5.0 out of 5 stars[Please note: I wrote the Foreword for this book]A great book to turn web developers into AI developers
Reviewed in the United States on June 3, 2021
Gant has done something special with this book. In just 300 pages, he takes you end-to-end, in-depth through everything you need to know from an introduction to AI, understanding tensors, using them in the browser, deploying them, and more.
It ends with a capstone project (what a great idea, I might have to steal it for my next book!), where you can use Machine Learning to convert an image into a set of dice, like the attached picture.
How much fun is that?
I love this book because it is for a different audience than the traditional ML one. It starts with a great introduction to AI and then tells you about TensorFlow.js and how you can use it to build Machine Learning apps. Then, the mystery of Tensors is cracked open, and Gant leads you through some detailed examples of how you can convert images into Tensors for training and inference.
It guides you through the three main ways to get a working model.
First, you can find an existing model from TensorFlow Hub, and in Chapter 5, Gant leads you through using the inception model in JavaScript. Inception isn’t any toy model, though – it is a Convolutional Neural Network designed for image analysis and object detection. It’s not that long ago that it was state-of-the-art in research. And now it’s available in JavaScript!
Or, you can create your model from scratch, and Gant takes you through the code for defining layers, with deep neural networks to help predict numeric data (such as the famous titanic dataset) or Convolutional Neural networks for image classification.
Finally, there’s Transfer Learning, which could be the most exciting method for most developers, where you have a hybrid of both of the previous methods. You can stand on the shoulders of giants by using parts of an existing model, like Inception, but catered for your own needs.
When I started my Machine Learning journey, one frustration I had was that there was lots of material for creating models but relatively little for using them. The tutorial would end with a validation set showing how accurate the model was, and then it would move on to the next thing! I am delighted to say that this book does not fall into that pattern! So, if you want to build a browser-based app that uses a model, you’ll get lots of code showing you how!
For example, Chapter 6 shows you how to use the webcam in the browser, capturing frames and passing them to a model for classification. Chapter 10 shows you how to create a basic sketchpad for drawing images that a model can interpret.
Whether you’re an experienced Machine Learning expert, looking to see how to apply JavaScript to help solve your problems, or a JavaScript developer who wants to enter the wonderful world of ML, this book is for you.
Images in this review
- Reviewed in the United States on April 27, 2022Format: PaperbackVerified Purchasevery fast delivery but it's not a new book, pages are clearly manipulated and damaged by some liquid.
very fast delivery but it's not a new book, pages are clearly manipulated and damaged by some liquid.
Images in this review
- Reviewed in the United States on June 23, 2021Format: Paperback[Disclosure: I received a free copy for review!]
Most machine learning books are going to ask you to delve into the realm of linear algebra and theory, but Gant does his level best to steer clear of confusing mathematics here. This book focuses on practical methods for using Tensorflow and also serves as a great introduction to high-level machine learning concepts. The writing is incredibly accessible and the explanations are fun which makes this an easy read for most as long as you're already familiar with JavaScript.
For me, probably the biggest value here is a demystification of the inner-workings of machine learning. Sure, it's all about math internally, but this book excels at explaining how ML works beyond the math, meaning that you'll walk away with a greater understanding of how things like augmented reality, natural language processing, and image recognition work. You'll begin to notice how much machine learning has worked its way into our everyday lives through things like proximity sensors and lane assist on cars, voice commands in smart devices, etc.
As far as projects go, Gant guides you through leveraging existing models all the way through building and training your own by the end of the book. He even goes as far as providing examples in NodeJS and the browser so you're not limited to a certain environment.
Reading this won't make you a master of machine learning, a data scientist, or a mathematician, but you'll definitely be primed for harder texts on the subject should you choose to continue down that path.
Overall, if you'd like to get into machine learning as a front-end web developer, this is your book.
- Reviewed in the United States on June 3, 2021Format: PaperbackThe book reads like a video game, with small missions of ever-growing complexity. Each mission depends on skills you've previously unlocked. I found the story and the pace to be entertaining as well as educational. If you've ever seen Gant speak at a conference or online, you know you're in for a treat.
The source code associated with the book is clearly organized and documented. The code starts as early as chapter 2, where you detect trucks and toxic language. From the moment you open the book, you feel immersed in a new and wonderful universe. At no time did I feel limited by math or any other didactic villainy.
I would highly recommend this book for any web developer who's interested in TensorFlow.js. Just read the praise on the first page! I'm not alone.
Top reviews from other countries
SalimReviewed in France on September 9, 20245.0 out of 5 stars Perfect
Format: KindleVerified PurchaseExactly what Javascript/Typescript Developer need to discover tensorflow with js/ts
Computational ScientistReviewed in the United Kingdom on April 14, 20255.0 out of 5 stars Run a neural network in the browser!
Format: PaperbackVerified PurchaseAwesome book! The author is a little "informal" in their writing style, but they cover so many great topics. Whether you want to build and run your own neutral networks in the browser or on Node, or if you want to fine-tune models or even use Teachable Machine, this book has great code samples and explanations.
Amazon CustomerReviewed in Canada on October 22, 20215.0 out of 5 stars Simplified and to the point
Format: PaperbackVerified PurchaseWas a really quick and easy read, helped me reach a clear understanding around deep learning concepts with Javascript. Solid introduction.
MohamedReviewed in Germany on August 26, 20215.0 out of 5 stars It's great book 📚
Format: PaperbackVerified PurchaseIt's great book for everyone how is getting started in Ml and knws the basic if JavaScript.The media could not be loaded.
The Book explain everything in peaceful way no complications or unnecessary staff. But it's worth noting it's great start but not for advanced users.
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Jozef StepienReviewed in Poland on April 13, 20234.0 out of 5 stars Merytorycznie - OK
Format: PaperbackVerified PurchaseMerytorycznie pozycja w porządku. Natomiast niechlujny sposób pakowania, pomimo poboru opłaty za pakowanie - uszkodzona okładka książki.














