Deep Learning with JavaScript: Neural networks in TensorFlow.js cover
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About this Book


Who should read this book

This book is written for programmers who have a working knowledge of JavaScript, from prior experience with either web frontend development or Node.js-based backend development, and wish to venture into the world of deep learning. It aims to satisfy the learning needs of the following two subgroups of readers:

  • JavaScript programmers who aspire to go from little-to-no experience with machine learning or its mathematical background, to a decent knowledge of how deep learning works and a practical understanding of the deep-learning workflow that is sufficient for solving common data-science problems such as classification and regression
  • Web or Node.js developers who are tasked with deploying pre-trained models in their web app or backend stack as new features

For the first group of readers, this book develops the basic concepts of machine learning and deep learning in a ground-up fashion, using JavaScript code examples that are fun and ready for fiddling and hacking. We use diagrams, pseudo-code, and concrete examples in lieu of formal mathematics to help you form an intuitive, yet firm, grasp of the foundations of how deep learning works.

How this book is organized: A roadmap

About the code

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