Hands On Machine Learning With Tensorflow Js
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Hands On Machine Learning With Tensorflow Js
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Author : Kai Sasaki
language : en
Publisher:
Release Date : 2019-11-27
Hands On Machine Learning With Tensorflow Js written by Kai Sasaki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-27 with Computers categories.
Get hands-on with the browser-based JavaScript library for training and deploying machine learning models effectively Key Features Build, train and run machine learning models in the browser using TensorFlow.js Create smart web applications from scratch with the help of useful examples Use flexible and intuitive APIs from TensorFlow.js to understand how machine learning algorithms function Book Description TensorFlow.js is a framework that enables you to create performant machine learning (ML) applications that run smoothly in a web browser. With this book, you will learn how to use TensorFlow.js to implement various ML models through an example-based approach. Starting with the basics, you'll understand how ML models can be built on the web. Moving on, you will get to grips with the TensorFlow.js ecosystem to develop applications more efficiently. The book will then guide you through implementing ML techniques and algorithms such as regression, clustering, fast Fourier transform (FFT), and dimensionality reduction. You will later cover the Bellman equation to solve Markov decision process (MDP) problems and understand how it is related to reinforcement learning. Finally, you will explore techniques for deploying ML-based web applications and training models with TensorFlow Core. Throughout this ML book, you'll discover useful tips and tricks that will build on your knowledge. By the end of this book, you will be equipped with the skills you need to create your own web-based ML applications and fine-tune models to achieve high performance. What you will learn Use the t-SNE algorithm in TensorFlow.js to reduce dimensions in an input dataset Deploy tfjs-converter to convert Keras models and load them into TensorFlow.js Apply the Bellman equation to solve MDP problems Use the k-means algorithm in TensorFlow.js to visualize prediction results Create tf.js packages with Parcel, Webpack, and Rollup to deploy web apps Implement tf.js backend frameworks to tune and accelerate app performance Who this book is for This book is for web developers who want to learn how to integrate machine learning techniques with web-based applications from scratch. This book will also appeal to data scientists, machine learning practitioners, and deep learning enthusiasts who are looking to perform accelerated, browser-based machine learning on Web using TensorFlow.js. Working knowledge of JavaScript programming language is all you need to get started.
Hands On Machine Learning With Javascript
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Author : Burak Kanber
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-29
Hands On Machine Learning With Javascript written by Burak Kanber 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 2018-05-29 with Computers categories.
A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript Key Features Solve complex computational problems in browser with JavaScript Teach your browser how to learn from rules using the power of machine learning Understand discoveries on web interface and API in machine learning Book Description In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier, and many more to design smarter applications. What you will learn Get an overview of state-of-the-art machine learning Understand the pre-processing of data handling, cleaning, and preparation Learn Mining and Pattern Extraction with JavaScript Build your own model for classification, clustering, and prediction Identify the most appropriate model for each type of problem Apply machine learning techniques to real-world applications Learn how JavaScript can be a powerful language for machine learning Who this book is for This book is for you if you are a JavaScript developer who wants to implement machine learning to make applications smarter, gain insightful information from the data, and enter the field of machine learning without switching to another language. Working knowledge of JavaScript language is expected to get the most out of the book.
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.
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
Practical Machine Learning In Javascript
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Author : Charlie Gerard
language : en
Publisher: Apress
Release Date : 2020-11-17
Practical Machine Learning In Javascript written by Charlie Gerard and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Computers 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 knowledge as a web developer, you’ll add a whole new field of development to your tool 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. 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. What You'll Learn Use the JavaScript framework for ML Build machine learning applications for the web Develop dynamic and intelligent web content Who This Book Is For Web developers and who want a hands-on introduction to machine learning in JavaScript. A working knowledge of the JavaScript language is recommended.
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.
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.
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.
Artificial Intelligence Programming With Python
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Author : Perry Xiao
language : en
Publisher: John Wiley & Sons
Release Date : 2022-02-21
Artificial Intelligence Programming With Python written by Perry Xiao and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-21 with Computers categories.
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learning Expansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learning Practical AI and Python “cheat sheet” quick references This hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
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