Tensorflow Js In 3 Hours
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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].
Simulation Modeling And Analysis Sixth Edition
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Author : Averill M. Law
language : en
Publisher: McGraw Hill Professional
Release Date : 2025-02-21
Simulation Modeling And Analysis Sixth Edition written by Averill M. Law and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-21 with Technology & Engineering categories.
Comprehensive, state-of-the-art coverage of every important simulation technique This fully-revised book has the most comprehensive and up-to-date coverage of all aspects of a simulation study. Equally well suited for use in university courses, simulation practice, and self-study, the book offers clear and intuitive explanations as well as 300 figures, 218 examples, and 217 problems. You will get detailed discussions on modeling and simulation, simulation software, model verification and validation, input modeling, random-number and variate generation, statistical design and analysis of simulation experiments, experimental design, simulation optimization, agent-based simulation, machine learning, and much more. Authored by an operations research analyst and industrial engineer with more than 40 years of experience, Simulation Modeling and Analysis is widely regarded as the “bible” of simulation and now has more than 178,000 copies in print and 23,700 citations. This sixth edition has been streamlined, with several chapters downsized to eliminate outdated simulation programs or statistical techniques that are rarely used in practice and are unnecessarily complicated. Most analyses of simulation output data can now be done using three simple and familiar statistical formulas or expressions. A new chapter covers AI and machine learning and their application to simulation. Covers what are arguably the three most-innovative and popular simulation-software packages: AnyLogic, FlexSim, and Simio Includes a set of instructor’s resources Has been used at universities such as University of California-Berkeley, Stanford, Georgia Tech, Michigan, Cornell, Purdue, Virginia Tech, Penn State, Wisconsin, Columbia, Texas A&M, Washington, and Johns Hopkins Written by a world-class expert in the field and an experienced educator who has presented more than 550 simulation and statistics short courses in 20 countries
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 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
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.
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.
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 : 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 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.