TensorFlow.js Deep Learning Projects: Exciting projects for making easy-to-run machine learning and deep learning models in your browser

Become well-versed with advanced neural network architectures to design, develop, and deploy smart web applications Key Features Build lightweight machine learning models and run them directly on the browser Become proficient in machine learning tasks to make your web applications dynamic and analytics-driven Create advanced neural networks, train pre-trained models and get to grips with TensorFlow.js features Book DescriptionTensorFlow.js is an open source machine learning (ML) library from Google for performing browser-based ML. It enables developers to create, run, and embed complex ML models in the browser. With this book, you'll learn to integrate autonomous and faster analytical capabilities in the browser efficiently. The book starts from the basics, explaining the fundamentals of TensorFlow.js and machine learning, before building up to the advanced concepts. You'll understand how to develop and deploy lightweight ML models. The book then takes you through developing smart apps directly on web browsers by using deep learning and TensorFlow.js features. You'll not only learn to implement neural network architectures such as RNNs, GRUs, and LSTMs, but also work through end-to-end projects, right from creating a speech recognizer and web app for text generation, to making a synthetic image generator system and simulation web app. Covering all the steps involved, from model building to deployment, along with best practices, you'll gain plenty of practical experience. Finally, you'll use multiple neural network architectures to build a game that can re-train your model with multiple pictures of gestures. By the end of this deep learning book, you'll have knowledge of TensorFlow.js and browser-based ML and be able to easily embed ML in your JavaScript projects. What you will learn Understand the TensorFlow.js API and its usage in the deep learning domain Explore model training and data visualization in TensorFlow.js Create a sentimental analysis web app with multiple models Generate interesting synthetic images using GANs Implement a self-balancing simulation web app using reinforcement learning Build exciting self-learning games using multiple deep learning neural network architectures Detect poses in real-time using PoseNet Develop interesting effects such as making parts of an image invisible in a frame with the BodyPix model Who This Book Is ForThis book is for JavaScript developers and front-end developers who want to add smart machine learning and deep learning features to their existing browser applications. It will also be useful for data scientists and machine learning professionals who want to learn deep learning to build powerful web applications. Working knowledge of the JavaScript programming language and machine learning basics is expected.