Learning Tensorflow Js
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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
Introduction To Machine Learning With Tensorflow Js
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Author : Asim Hussain
language : en
Publisher:
Release Date : 2021-02-28
Introduction To Machine Learning With Tensorflow Js written by Asim Hussain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-28 with categories.
Many exciting things are happening with machine learning, from which, until recently, JavaScript developers were largely shut out. However, things are changing, now if you can do "npm install @tensorflow/tfjs", you can do machine learning. This absolute beginner book takes someone with no knowledge of Machine Learning and teaches them the basics. The book will teach how to use the TensorFlow.JS library, a complete re-write of the popular TensorFlow package in JavaScript. If you want to get a taste of what this exciting field has to offer, if you want to talk to other AI specialists in a language they understand, then this book is for you. You'll learn: - What are Neural Networks, and how is it related to Machine Learning? - What is TensorFlow.js, and how to use it? - The essential mathematics. - How to build and train a neural network to solve regression and classification tasks. - How to use pre-trained models. - How to use transfer learning to generate powerful machine learning models in the browser, without expensive computation on servers. You will learn hands-on by creating 6 different applications, including a handwriting recogniser and a webcam-based hand-sign recogniser. Taught by Asim Hussain, co-organiser of the AI JavaScript London Meetup and co-creator of https://aijs.rocks and community member of the W3C Machine Learning Group.
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.
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.
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
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].
Javascript For Machine Learning
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Author : Anthony Hopkins
language : en
Publisher: Independently Published
Release Date : 2025-08-15
Javascript For Machine Learning written by Anthony Hopkins and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-15 with Computers categories.
What if you could build web apps that don't just respond-but think? What if your JavaScript skills could unlock real-time image recognition, smart chatbots, and predictive analytics-without switching to Python or needing massive server infrastructure? JavaScript for Machine Learning is your hands-on guide to creating intelligent, browser-based applications powered by TensorFlow.js and Brain.js. Whether you're predicting stock prices, classifying images, or building a chatbot that understands sentiment, this book shows you exactly how to make it happen-step-by-step. Inside, you'll discover how to: Master machine learning concepts without drowning in math-heavy jargon Build neural networks in the browser with TensorFlow.js and Brain.js Preprocess and handle data for real-time predictions Create complete ML-powered apps-image classifiers, chatbots, time-series predictors, and more Optimize models for speed, privacy, and mobile performance Deploy your intelligent web apps like a pro With real-world projects and clear explanations, you'll learn by building, not just reading. By the end, you'll have a portfolio of production-ready, ML-powered web applications-and the confidence to create your own. If you can write JavaScript, you can build AI. If you can build AI, you can change the way people experience the web. Don't just code websites-teach them to learn. Buy JavaScript for Machine Learning now and start building smart web apps today.
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.
Hands On Machine Learning With Tensorflow Js
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Author : Arish Ali
language : en
Publisher:
Release Date : 2018
Hands On Machine Learning With Tensorflow Js written by Arish Ali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"Machine learning is a growing and in-demand skill, but so far JavaScript developers have not been able to take advantage of it due to the steep learning curve involved in learning a new language. TensorFlow.js is a great way to begin learning machine learning in the browser with TensorFlow.js. It allows you to operate offline to train new models and retrain existing models. This course covers most of the major topics in machine learning and explains them with the help of TensorFlow.js implementations. The course is focused on the result-oriented nature of most JavaScript developers, and focuses on TensorFlow.js to the fullest in the least amount of time. At the end of the course, you'll evaluate and implement the right model to design smarter applications."--Resource description page.