Learning 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.
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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.
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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.
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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.
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
Learning 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.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, 2021
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.
A great book to turn web developers into AI developers
Reviewed in the United States on June 3, 2021
[Please note: I wrote the Foreword for this book]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, 2022
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, 2021
Top reviews from other countries
Anzbert
Best book for ML beginners familiar with JavaScript
Reviewed in Australia on July 17, 2021
