Practical Tensorflow Js
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Practical Tensorflow Js
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Author : Juan De Dios Santos Rivera
language : en
Publisher: Apress
Release Date : 2020-10-03
Practical Tensorflow Js written by Juan De Dios Santos Rivera and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-03 with Computers categories.
Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web apps. The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis. Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js. What You'll Learn Build deep learning products suitable for web browsers Work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN) Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis Who This Book Is For Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.
Practical Machine Learning In Javascript
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Author : Charlie Gerard
language : en
Publisher:
Release Date : 2021
Practical Machine Learning In Javascript written by Charlie Gerard and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Build machine learning web applications without having to learn a new language. This book will help you develop basic knowledge of machine learning concepts and applications. You'll learn not only theory, but also dive into code samples and example projects with TensorFlow.js. Using these skills and your already honed skills as a web developer, you'll add a whole new field of development to your skill set. This will give you a more concrete understanding of the possibilities offered by machine learning. Discover how ML will impact the future of not just programming in general, but web development specifically. Get started in machine learning with web technologies. Machine learning is currently one of the most exciting technology fields with the potential to impact industries from health to home automation to retail, and even art. Google has now introduced TensorFlow.js-an iteration of TensorFlow aimed directly at web developers. Practical Machine Learning in JavaScript will help you stay relevant in the tech industry with new tools, trends, and best practices. You will: Use the JavaScript framework for ML Build machine learning applications for the web Develop dynamic and intelligent web content.
Tensorflow Js In 3 Hours
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Author : Jakub Konczyk
language : en
Publisher:
Release Date : 2019
Tensorflow Js In 3 Hours written by Jakub Konczyk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Get up and running with Tensorflow.js in your browser About This Video Get up and running with Tensorflow.js quickly with practical real-world examples in a web browser Tackle the most common Machine Learning problems using Tensorflow.js Discover how to quickly include Deep Learning functionality in your own web applications in a web browser using pre-trained models In Detail In this course, you'll learn how to use Tensorflow.js for a variety of the most popular Deep Learning tasks and use them in your own web browser. You'll start by learning how to classify images using commonly used Convolutional Neural Networks. And you'll get up and running fast using a pre-trained model. Then you'll explore yet another popular deep learning architecture called Long Short-Term Memory Recurrent Neural Network. This time you'll classify text typed by a user in real time. Moving on, you'll work with audio data using a specific type of CNN. Then we'll jump into methods to improve the results of our models by firstly looking at transfer learning. Here you'll improve the performance of your model quickly by using a pre-trained model as a base and performing short, focused training. By the end of this course, you'll have the skills to use Tensorflow.js and train your own personal models using only a web browser. Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/TensorFlow.js-in-3-Hours . If you require support please email: [email protected].
Deep Learning With Javascript
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Author : Stanley Bileschi
language : en
Publisher: Simon and Schuster
Release Date : 2020-01-24
Deep Learning With Javascript written by Stanley Bileschi and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-24 with Computers categories.
Summary Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of the TensorFlow library, this new book provides fascinating use cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Foreword by Nikhil Thorat and Daniel Smilkov. About the technology Running deep learning applications in the browser or on Node-based backends opens up exciting possibilities for smart web applications. With the TensorFlow.js library, you build and train deep learning models with JavaScript. Offering uncompromising production-quality scalability, modularity, and responsiveness, TensorFlow.js really shines for its portability. Its models run anywhere JavaScript runs, pushing ML farther up the application stack. About the book In Deep Learning with JavaScript, you’ll learn to use TensorFlow.js to build deep learning models that run directly in the browser. This fast-paced book, written by Google engineers, is practical, engaging, and easy to follow. Through diverse examples featuring text analysis, speech processing, image recognition, and self-learning game AI, you’ll master all the basics of deep learning and explore advanced concepts, like retraining existing models for transfer learning and image generation. What's inside - Image and language processing in the browser - Tuning ML models with client-side data - Text and image creation with generative deep learning - Source code samples to test and modify About the reader For JavaScript programmers interested in deep learning. About the author Shanging Cai, Stanley Bileschi and Eric D. Nielsen are software engineers with experience on the Google Brain team, and were crucial to the development of the high-level API of TensorFlow.js. This book is based in part on the classic, Deep Learning with Python by François Chollet. TOC: PART 1 - MOTIVATION AND BASIC CONCEPTS 1 • Deep learning and JavaScript PART 2 - A GENTLE INTRODUCTION TO TENSORFLOW.JS 2 • Getting started: Simple linear regression in TensorFlow.js 3 • Adding nonlinearity: Beyond weighted sums 4 • Recognizing images and sounds using convnets 5 • Transfer learning: Reusing pretrained neural networks PART 3 - ADVANCED DEEP LEARNING WITH TENSORFLOW.JS 6 • Working with data 7 • Visualizing data and models 8 • Underfitting, overfitting, and the universal workflow of machine learning 9 • Deep learning for sequences and text 10 • Generative deep learning 11 • Basics of deep reinforcement learning PART 4 - SUMMARY AND CLOSING WORDS 12 • Testing, optimizing, and deploying models 13 • Summary, conclusions, and beyond
Artificial Intelligence For Human Computer Interaction A Modern Approach
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Author : Yang Li
language : en
Publisher: Springer Nature
Release Date : 2021-11-04
Artificial Intelligence For Human Computer Interaction A Modern Approach written by Yang Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-04 with Computers categories.
This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.
Learning Tensorflow Js
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Author : Gant Laborde
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-10
Learning Tensorflow Js written by Gant Laborde and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-10 with Computers categories.
Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google 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-readydeep 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 Use resources to convert, train, and manage machine learning data Build and train your own training models from scratch
Hands On Machine Learning With Tensorflow Js
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Author : Kai Sasaki
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-27
Hands On Machine Learning With Tensorflow Js written by Kai Sasaki and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-27 with Computers categories.
Hands-On Machine Learning with TensorFlow.js is a comprehensive guide that will help you easily get started with machine learning algorithms and techniques using TensorFlow.js. By the end of this book, you will be able to create and optimize your own web-based machine learning applications using practical examples.
Hands On Tensorflow Js Keras React
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Author : Marcus C Lauritsen
language : en
Publisher: Independently Published
Release Date : 2025-08-11
Hands On Tensorflow Js Keras React written by Marcus C Lauritsen and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-11 with Computers categories.
Hands-On TensorFlow.js, Keras & React: Create Modern Web Apps with AI and Deep Learning Does AI feel out of reach-too complex, too math-heavy, or "only for Python pros"? This beginner-friendly guide shows you how to build smart, interactive web apps in the browser using tools you already love: JavaScript, TensorFlow.js (with Keras-style APIs), and React. No prior AI experience required. If you can follow step-by-step instructions, you can ship your first browser-based AI feature with confidence. You'll learn by doing-moving from plain-English explanations to small, focused projects you can click, see, and improve. Along the way, you'll discover why on-device inference matters for privacy and speed, how to wire models cleanly into React components, and how to deliver production-ready UX with loading, empty, and error states that feel polished and humane. What you'll build and understand AI in the browser, explained simply: Tensors, layers, training vs. inference, transfer learning-without drowning in theory. TensorFlow.js + Keras workflow: Load, fine-tune, and run models with clear, Keras-style APIs. Real projects: Image classification (MobileNet), a simple sentiment analyzer, and live webcam demos-customizable and ready to extend. React integration that feels natural: Hooks, lazy loading, caching hints, and clean state for predictions and UI feedback. Performance & deployment: WebGL/WASM backends, model size optimization, quantization, and PWA packaging for fast, offline-capable apps. Responsible by design: Practical tips for accessible UI, user privacy, and basic model security in the browser. Why beginners succeed with this book Step-by-step guidance that explains the why behind each step. Mistakes welcomed: We debug together; every bump becomes a small win. Modern stack, real results: JavaScript + React + TensorFlow.js means less setup, more building. Who it's for Curious beginners, web developers, and JS learners who want practical machine learning in JavaScript-without switching stacks. Python folks looking to bring models to the web will feel right at home with the Keras-style approach. Ready to build something smart-today? Open the book, follow the steps, and launch your first intelligent React app. Your AI journey starts in the browser.
Coding Examples From Simple To Complex
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Author : Paul A. Gagniuc
language : en
Publisher: Springer Nature
Release Date : 2024-04-29
Coding Examples From Simple To Complex written by Paul A. Gagniuc and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
This book provides a comprehensive guide to JavaScript, which stands as the cornerstone of modern programming and is the main computer language driving the Internet. The author introduces readers to the rich world of JavaScript, taking them on a journey from the fundamentals to advanced topics, equipping them with the knowledge and skills needed to become a proficient science and engineering oriented JavaScript developer. The book provides a treasure trove of practical examples, meticulously crafted to deepen the reader understanding of JavaScript. This comprehensive exploration is designed to cater to novice learners as well as mature developers and scientists, equipping them with the requisite knowledge and competencies to harness the JavaScript full potential in their respective projects. This book is part of a series of works designed to present both the examples and their explanations in various computer languages, as close to a mirror version as possible.
Javascript Programming For Building Deep Learning Models With Deeplearn Js And Tensorflow Js
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Author : Cesar J Burnett
language : en
Publisher: Independently Published
Release Date : 2025-08-05
Javascript Programming For Building Deep Learning Models With Deeplearn Js And Tensorflow Js written by Cesar J Burnett and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-05 with Computers categories.
Have you ever wondered how your favorite websites seem to read your mind, or how a simple text box can write a story for you? We've all seen the magic of AI, but the journey from a brilliant idea to a working application can feel like a steep, technical mountain. Most books on deep learning are locked behind complex languages and intimidating math, leaving countless creators and web developers on the sidelines. This book is your all-access pass. It cuts through the jargon, empowering you with the tools you already know-JavaScript-to build, train, and deploy powerful AI models. You'll go from understanding core concepts to creating real, hands-on applications, including image classifiers, live webcam tools, and even recommendation systems. This is more than just theory; it's a practical, step-by-step guide that puts the power of deep learning directly into your hands. Ready to build the future of intelligent web applications? Your journey starts now.