WRITING
Published in Print
Authorship
Combining the demand for AI with the ubiquity of JavaScript was inevitable. With Google’s TensorFlow.js 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 and other tools
- Use resources to convert, train, and manage machine learning data
- Start building and training your own training models from scratch
- Learn how to create your own image classification models
- Examine transfer learning: retraining an advanced model to perform a new task
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Amazon Author Page: https://www.amazon.com/author/gantlaborde
Praise for Learning TensorFlow.js
From the book’s early reviewers, including Google’s TensorFlow.js team
“What Gant has done with this book is to cut to the chase, and teach you the important stuff you need to know while keeping you firmly within the web developer role, using JavaScript and the Browser.”
“Machine learning has the potential to influence every industry out there. This book enables you to take your first steps with TensorFlow.js, allowing any JavaScript developer to gain superpowers in their next web application and beyond. This book is a great introduction to machine learning using TensorFlow.js that also applies what you learn with real world examples that are easy to digest.”
“Gant’s ability to navigate explaining the 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.”
“This is a much-needed introduction to TensorFlow.js, with great examples, amazing illustrations, and insightful quotes at the beginning of each chapter. A must-read for anyone who’s serious about doing AI with JavaScript.”
“I wish that I’d had this book myself to learn neural networks and TensorFlow.js in the past! Astonishingly simple and beautifully written, it goes from zero to doing a full capstone project in 12 short chapters. A must-have in every library.”
“Machine learning for the web is still in its infancy, and books such as the one you’re holding right now are super important. As a machine learning engineer working on ML tools for the JavaScript environment, my top recommendation for web developers seeking to add ML to their projects is definitely Learning TensorFlow.js.”
“I’m delighted to have read Learning TensorFlow.js. It is without doubt a good way to get out of my comfort zone of backend engineering and try out building some exciting frontend applications, leveraging the power of the book’s content about TensorFlow.js as the go-to framework for ML web applications.”
“This book serves as the right introduction to building small deep learning models fit for web and mobile based applications. The examples in the book along with the detailed explanation will make your learning smooth and fun.”
