Javascript Programming For Building Deep Learning Models
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Javascript Programming For Building Deep Learning Models
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Author : AGENTA. MILLO
language : en
Publisher: Independently Published
Release Date : 2025-03-10
Javascript Programming For Building Deep Learning Models written by AGENTA. MILLO and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-10 with Computers categories.
Unlock the immense power of Artificial Intelligence with JavaScript! JavaScript Programming for Building Deep Learning Models is the ultimate guide to mastering AI development using JavaScript. This comprehensive book empowers developers with the tools and knowledge needed to create advanced deep learning models, all while leveraging JavaScript's unparalleled accessibility and web integration. Dive deep into the world of AI and explore its potential with real-world applications. From neural networks to computer vision, NLP, and reinforcement learning, this book takes you step-by-step through essential concepts and complex models. Learn to build and train models using TensorFlow.js, and discover how to bring powerful AI to web browsers and edge devices for real-time, client-side applications. Whether you're building your first neural network or deploying sophisticated deep learning solutions, this book will guide you every step of the way. With hands-on projects and practical exercises, you'll develop expertise in the most cutting-edge AI techniques. In this book, you will: Master the fundamentals of deep learning, neural networks, and their applications. Discover why JavaScript is a game-changer in AI development. Explore advanced deep learning models, including CNNs, RNNs, GANs, and Transformers. Learn how to create real-time applications like image recognition, chatbots, and even self-learning systems. Implement deep learning with TensorFlow.js to run models directly in web browsers or Node.js environments. Optimize and scale models for real-world applications, from edge computing to cloud deployment. Perfect for developers eager to harness the power of JavaScript for AI, this book provides both foundational knowledge and cutting-edge techniques for building AI-powered systems. Start your journey into the world of deep learning today and unlock the potential of AI in web development with JavaScript! Why Choose This Book? Practical, hands-on approach with code examples and exercises Clear explanations for both beginners and advanced learners Insights on optimizing performance and scaling AI models Real-world applications, including NLP, image recognition, and chatbots Learn to deploy AI models directly to browsers and edge devices Prepare to push the boundaries of AI development with JavaScript Programming for Building Deep Learning Models!
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
Principles And Labs For Deep Learning
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Author : Shih-Chia Huang
language : en
Publisher: Academic Press
Release Date : 2021-07-06
Principles And Labs For Deep Learning written by Shih-Chia Huang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-06 with Science categories.
Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of results. The structured methods and labs provided by Dr. Huang and Dr. Le enable readers to become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications, and TensorFlow Hub. Each chapter has one corresponding Lab with step-by-step instruction to help the reader practice and accomplish a specific learning outcome. Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning. - Introduces readers to the usefulness of neural networks and Deep Learning methods - Provides readers with in-depth understanding of the architecture and operation of Deep Convolutional Neural Networks - Demonstrates the visualization needed for designing neural networks - Provides readers with an in-depth understanding of regression problems, binary classification problems, multi-category classification problems, Variational Auto-Encoder, Generative Adversarial Network, and Object detection
Building Data Driven Applications With Danfo Js
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Author : Rising Odegua
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-24
Building Data Driven Applications With Danfo Js written by Rising Odegua 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 2021-09-24 with Computers categories.
Get hands-on with building data-driven applications using Danfo.js in combination with other data analysis tools and techniques Key FeaturesBuild microservices to perform data transformation and ML model serving in JavaScriptExplore what Danfo.js is and how it helps with data analysis and data visualizationCombine Danfo.js and TensorFlow.js for machine learningBook Description Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications. Starting with an overview of modern JavaScript, you'll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You'll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you'll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you'll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js. By the end of this app development book, you'll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser. What you will learnPerform data experimentation and analysis with Danfo.js and DnotebookBuild machine learning applications using Danfo.js integrated with TensorFlow.jsConnect Danfo.js with popular database applications to aid data analysisCreate a no-code data analysis and handling system using internal librariesDevelop a recommendation system with Danfo.js and TensorFlow.jsBuild a Twitter analytics dashboard for sentiment analysis and other types of data insightsWho this book is for This book is for data analysts, data scientists, and JavaScript developers who want to create data-driven applications in the JavaScript/Node.js environment. Intermediate-level knowledge of JavaScript programming and data science using pandas is expected.
Javascript Programming
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Author : K. Mitts
language : en
Publisher: Code Academy
Release Date : 2025-06-02
Javascript Programming written by K. Mitts and has been published by Code Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-02 with Computers categories.
Take your JavaScript skills from theory to practice with JavaScript Programming by K. Mitts. This project-based guide empowers you to build real-world web applications using modern JavaScript techniques. From interactive forms and dynamic content to API integration and full-featured projects, this book walks you through each step with hands-on examples and clean, reusable code. Ideal for learners who want to turn coding knowledge into live, working websites and web apps.
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 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.
Mastering Ai App Development With Mern Stack Step Into The Future Of App Development By Building Intelligent Ai Powered Applications With Mern Stack And Tensorflow Js For Seamless User Experiences
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Author : Anik Acharjee
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-11-05
Mastering Ai App Development With Mern Stack Step Into The Future Of App Development By Building Intelligent Ai Powered Applications With Mern Stack And Tensorflow Js For Seamless User Experiences written by Anik Acharjee and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Computers categories.
Transform Your Web App Development Journey with MERN and AI Key Features● Utilize AI for code generation, debugging, and optimizing performance in MERN applications.● Build AI-powered web apps with real-time data processing and user behavior insights.● Integrate AI capabilities seamlessly with MongoDB, Express.js, React, and Node.js for scalable web solutions. Book DescriptionWith AI applications driving a projected $15.7 trillion boost to the global economy by 2030, combining AI with the popular MERN stack has become a game-changer for developers and businesses alike. Mastering AI App Development with MERN Stack is a hands-on guide designed for developers ready to bring AI capabilities to their MERN applications, covering everything from foundational machine learning to advanced, real-world solutions. Starting with the essentials of setting up a MERN development environment, the book guides readers through machine learning basics in JavaScript, enabling AI integration with Node.js and TensorFlow.js. Each chapter provides practical insights into building intelligent interfaces with React, effective data handling with MongoDB, and AI middleware using Express.js. Readers will learn to create features like AI-powered chatbots, image and voice recognition, and personalized recommendation systems. Real-world scenarios and case studies demonstrate how AI can elevate MERN applications. With guidance on security practices, deployment, and scaling, this book is a complete toolkit for building secure, production-ready AI solutions with MERN. Mastering AI with the MERN Stack empowers developers to unlock the full potential of AI in the MERN ecosystem, creating innovative, impactful applications for an AI-driven world. What you will learn● Integrate AI into MERN applications for improved user experiences.● Build AI-powered web apps using the MERN stack effectively.● Implement real-time data processing and personalized content features.● Leverage pre-trained AI models for language and analytics tasks.● Design scalable AI architectures to enhance performance and capacity. Table of Contents1. Introduction to AI and the MERN Ecosystem2. Setting Up the MERN Development Environment3. Fundamentals of Machine Learning with JavaScript4. Implementing AI with Node.js and TensorFlow.js5. Creating Intelligent User Interfaces with React6. Data Management for AI with MongoDB7. Building AI Middleware with Express.js8. Crafting AI-Powered Chatbots9. Image and Voice Recognition Capabilities10. Personalization with Recommendation Systems11. Deploying MERN and AI Applications12. Security Practices for AI-Enabled MERN Applications13. Scaling AI Features in Production14. Emerging Trends in AI and MERN Development15. Case Studies and Real-World Success Stories Index
Deep Learning And Its Applications
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Author : Dr. S. Manikandan
language : en
Publisher: Quing Publications
Release Date : 2022-12-30
Deep Learning And Its Applications written by Dr. S. Manikandan and has been published by Quing Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-30 with Computers categories.
Deep Learning and its Applications book chapter is intended to provide various deep insight about Deep learning in various applications. According to current Industry 4.0 standards, Deep learning on the emerging research area to give various services to IT and ITeS. In this book chapter various real time applications are taken for evaluating deep learning approach. Deep Learning is the subset of machine learning which has further learned results of artificial intelligent applications. Artificial Intelligent is the current scenario for making effective decisions. Here the applications are medical image processing, moving objects, image analysis, classification, clustering, prediction, and restoration used to identify various results. Based on each chapter different problems are taken for evaluation and apply different deep learning principles to find accuracy, precision, and score functions. Supervised and Unsupervised learning techniques, TensorFlow, Yolo classifier and Colabs are used to simulate the applications. In this book chapters are very useful for researchers, students, and faculty community to learn about Deep Learning in current trends.
Design Optimization Using Artificial Intelligence
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Author : Satya Ranjan Mishra
language : en
Publisher: CRC Press
Release Date : 2025-06-24
Design Optimization Using Artificial Intelligence written by Satya Ranjan Mishra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Technology & Engineering categories.
Design Optimization Using Artificial Intelligence serves as an insightful resource for understanding the transformative role of Artificial Intelligence (AI) in optimizing design processes across a variety of fields. This book explores foundational concepts, advanced methodologies, and real-world applications, offering a comprehensive guide to leveraging AI for innovative design solutions. Covering a broad spectrum of topics, the book examines algorithmic advancements, machine learning techniques, and optimization strategies that enhance design efficiency and accuracy. It delves into AI's applications in sustainable energy systems, biomedical innovations, image processing, cyber-security, and other critical domains, showcasing its ability to solve complex challenges with precision and creativity. The content bridges theoretical foundations with practical implementations, incorporating case studies that highlight successful applications of AI-driven design optimization. Readers will gain valuable insights into state-of-the-art tools, programming techniques, and frameworks that drive advancements in intelligent design systems. Features: Explores AI-driven methodologies for enhancing design accuracy and efficiency Discusses advanced machine learning techniques and optimization algorithms Highlights AI's applications in diverse fields such as energy systems, healthcare, image processing, and cyber-security Includes in-depth case studies to illustrate real-world implementations of AI in design optimization Investigates future trends and the potential of AI to transform traditional design processes Targeted at researchers, engineers, and students in the fields of artificial intelligence, computational science, and engineering, this book is an essential reference for anyone seeking to understand and utilize AI in the realm of design optimization. It provides the tools and knowledge necessary to harness AI's power for innovative, efficient, and intelligent design solutions.