Hands On Tensorflow Js Keras React
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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 : 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.
Analytics Engineering With Sql And Dbt
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Author : Rui Pedro Machado
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-12-08
Analytics Engineering With Sql And Dbt written by Rui Pedro Machado 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 2023-12-08 with Computers categories.
With the shift from data warehouses to data lakes, data now lands in repositories before it's been transformed, enabling engineers to model raw data into clean, well-defined datasets. dbt (data build tool) helps you take data further. This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL. Authors Rui Machado from Monstarlab and Hélder Russa from Jumia show you how to quickly deliver new data products by focusing more on value delivery and less on architectural and engineering aspects. If you know your business well and have the technical skills to model raw data into clean, well-defined datasets, you'll learn how to design and deliver data models without any technical influence. With this book, you'll learn: What dbt is and how a dbt project is structured How dbt fits into the data engineering and analytics worlds How to collaborate on building data models The main tools and architectures for building useful, functional data models How to fit dbt into data warehousing and laking architecture How to build tests for data transformations
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 And Pet Imaging Part 1 An Issue Of Pet Clinics
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Author : Babak Saboury
language : en
Publisher: Elsevier Health Sciences
Release Date : 2021-09-21
Artificial Intelligence And Pet Imaging Part 1 An Issue Of Pet Clinics written by Babak Saboury and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Medical categories.
Artificial Intelligence and PET Imaging, Part 1, An Issue of PET Clinics, E-Book
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
Full Stack Machine Learning
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Author : Haider Koele
language : en
Publisher: Independently Published
Release Date : 2025-11-21
Full Stack Machine Learning written by Haider Koele and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-21 with Computers categories.
Do you feel lost or overwhelmed by the idea of building smart web apps with machine learning? You're not alone. What if you could turn confusion into confidence-and bring AI projects to life, even if you've never coded before? Full-Stack Machine Learning: A Practical Guide to Building AI Web Applications with Python, Keras 3, and TensorFlow.js 4 is the friendly, step-by-step companion you've been waiting for. Written especially for beginners, this hands-on guide helps you unlock the world of artificial intelligence and web development-no experience required. Inside, you'll discover: Zero-to-hero guidance: Start from absolute basics and build up your skills in Python, Keras, and TensorFlow.js, one simple step at a time. Practical, real-world projects: Learn by doing with fun, achievable projects-like image classification, sentiment analysis, and interactive web apps you can actually share with friends. Confidence-building approach: Every chapter is packed with gentle explanations, encouraging advice, and troubleshooting tips to keep you moving forward, even when mistakes happen. End-to-end workflow: See how professional developers collect data, train models, and deploy them as real AI-powered web applications-in the browser and beyond. Modern, in-demand skills: Master the tools and concepts top employers look for, including deep learning, web deployment, data science in the browser, and full-stack machine learning. This book is for you if: You're a complete beginner or early learner wanting to break into AI and web development. You want practical experience-not just theory or overwhelming math. You're ready to turn curiosity into capability and build projects that truly work. Key features and benefits: Beginner-friendly machine learning projects: Written in plain English, with all jargon gently explained. Full-stack development made simple: Bridge the worlds of Python and JavaScript with clear, actionable steps. Mistakes are normal-progress is celebrated: This book normalizes challenges and shows you how to turn setbacks into learning opportunities. All the code you need: Copy, adapt, and expand on real examples designed for success. Supportive, nurturing style: Feel like you have a mentor guiding you from start to finish. Whether you dream of creating browser-based AI apps, want to land a tech job, or simply hope to demystify machine learning, this book delivers a complete, confidence-building roadmap. Start your journey today-discover just how fun, approachable, and rewarding full-stack machine learning can be! Your first real AI-powered app is closer than you think.
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.
Hands On Machine Learning With Scikit Learn Keras And Tensorflow
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Author : Aurélien Géron
language : en
Publisher:
Release Date : 2019
Hands On Machine Learning With Scikit Learn Keras And Tensorflow written by Aurélien Géron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Machine learning categories.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. The updated edition of this best-selling book uses concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow 2-to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Practitioners will learn a range of techniques that they can quickly put to use on the job. Part 1 employs Scikit-Learn to introduce fundamental machine learning tasks, such as simple linear regression. Part 2, which has been significantly updated, employs Keras and TensorFlow 2 to guide the reader through more advanced machine learning methods using deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. NEW FOR THE SECOND EDITION:Updated all code to TensorFlow 2Introduced the high-level Keras APINew and expanded coverage including TensorFlow's Data API, Eager Execution, Estimators API, deploying on Google Cloud ML, handling time series, embeddings and more With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released.
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.