Practical TensorFlow.js

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Develop and deploy deep learning web apps using the TensorFlow.js library, part of the larger TensorFlow framework. This book covers various tools that enhance TensorFlow.js, including TensorBoard, ml5js, and tfjs-vis, demonstrating how they integrate to create intelligent web applications. With web browsers being the most common platform for users, TensorFlow.js serves as a robust library for building browser-based AI solutions. By utilizing JavaScript, you can develop and serve deep learning applications directly in the browser. You will explore deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial networks (GAN). Through practical examples, you will apply these networks to use cases like image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis. The book also addresses traditional machine learning concepts, providing a foundational understanding, even though TensorFlow.js is primarily focused on deep learning. You will learn to build deep learning products for web browsers and work with a variety of algorithms and applications, enhancing your skills in this exciting field.