Deep Learning Projects With Javascript

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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

Tensorflow Machine Learning Projects

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Author : Ankit Jain
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30

Tensorflow Machine Learning Projects written by Ankit Jain 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 2018-11-30 with Computers categories.

Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key FeaturesUse machine learning and deep learning principles to build real-world projectsGet to grips with TensorFlow's impressive range of module offeringsImplement projects on GANs, reinforcement learning, and capsule networkBook Description TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts. By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work. What you will learnUnderstand the TensorFlow ecosystem using various datasets and techniquesCreate recommendation systems for quality product recommendationsBuild projects using CNNs, NLP, and Bayesian neural networksPlay Pac-Man using deep reinforcement learningDeploy scalable TensorFlow-based machine learning systemsGenerate your own book script using RNNsWho this book is for TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques

Deep Learning Projects With Javascript

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Author : Jakub Konczyk
language : en
Publisher:
Release Date : 2018

Deep Learning Projects With Javascript 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 2018 with categories.

"Getting started with deep learning seems overwhelming with so many options to choose from, so you might be wondering where to start, which tools to choose, and how to actually set them up? The good news is that you already have the key tool in front of you: your web browser with a powerful JavaScript engine inside it. And when you add the TensorFlow.js library to this combo, you can use deep learning methods via JavaScript in no time. In this course, you will through the process of getting started with TensorFlow.js to detect emotions with a lot of different types of data. You will start by learning how to build a deep learning tool to judge whether a piece of text is positive or negative. Since you will want tangible results quickly, you will use a pre-trained model to do that and include it into your own web application. You will move on to learn how to detect human emotions based only on pictures and voices using pre-trained models as well. Towards the end, you will learn how to modify a pre-trained model to train the emotional detector from scratch using your own data. By the end of this course you will know how to use Deep Learning models and train your own models from the ground up using JavaScript and the TensorFlow.js library."--Resource description page.

Hands On Python Deep Learning For The Web

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Author : Anubhav Singh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-05-15

Hands On Python Deep Learning For The Web written by Anubhav Singh 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 2020-05-15 with Computers categories.

Use the power of deep learning with Python to build and deploy intelligent web applications Key FeaturesCreate next-generation intelligent web applications using Python libraries such as Flask and DjangoImplement deep learning algorithms and techniques for performing smart web automationIntegrate neural network architectures to create powerful full-stack web applicationsBook Description When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python. Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages. By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices. What you will learnExplore deep learning models and implement them in your browserDesign a smart web-based client using Django and FlaskWork with different Python-based APIs for performing deep learning tasksImplement popular neural network models with TensorFlow.jsDesign and build deep web services on the cloud using deep learningGet familiar with the standard workflow of taking deep learning models into productionWho this book is for This deep learning book is for data scientists, machine learning practitioners, and deep learning engineers who are looking to perform deep learning techniques and methodologies on the web. You will also find this book useful if you’re a web developer who wants to implement smart techniques in the browser to make it more interactive. Working knowledge of the Python programming language and basic machine learning techniques will be beneficial.

Tensorflow Js Deep Learning Projects

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Author : MR UMANG. SHARMA
language : en
Publisher:
Release Date : 2021

Tensorflow Js Deep Learning Projects written by MR UMANG. SHARMA 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.

Ai For Web Developers

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Author : Hart Livingstone
language : en
Publisher: Independently Published
Release Date : 2025-11-09

Ai For Web Developers written by Hart Livingstone and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-09 with Computers categories.

AI is no longer a distant technology-it's here, and it's reshaping the way we build for the web. In AI for Web Developers: Machine Learning Projects with HTML, JavaScript, and TensorFlow.js, Hart Livingstone takes you on a hands-on journey into the intersection of artificial intelligence and modern web development. This book is written for curious developers who want to go beyond traditional coding and bring smart, interactive, and adaptive features directly into their web apps. With clear explanations, practical insights, and complete code examples, this guide turns complex AI concepts into simple, engaging learning experiences. You'll explore how to train and deploy machine learning models right in the browser, using nothing more than HTML, JavaScript, and TensorFlow.js - no heavy servers, no external dependencies. How to integrate AI and ML into front-end projects using TensorFlow.js The fundamentals of data handling, model training, and real-time predictions in the browser Building interactive projects - from image recognition apps to voice-controlled interfaces Tips for optimizing models, deploying AI-powered web apps, and testing across devices How to use WebGPU, WebAssembly, and Edge AI to push web performance to the next level Whether you're a web developer taking your first steps into AI or a machine learning enthusiast exploring browser-based solutions, this book gives you the tools, understanding, and confidence to build the intelligent web experiences of tomorrow. Instead of diving deep into mathematical theory, Hart focuses on real projects and creative problem-solving - helping you understand why things work, not just how. Every chapter feels like sitting beside a mentor who's as passionate about code as they are about teaching. You'll see how AI can make websites more personal, responsive, and even conversational. By the End of This Book you'll have a complete portfolio of browser-based AI projects and a strong grasp of how to design, build, and deploy machine learning apps - right from your code editor to the web. Get ready to merge creativity with intelligence. The future of web development starts right in your browser.

Scala Machine Learning Projects

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Author : Md. Rezaul Karim
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-31

Scala Machine Learning Projects written by Md. Rezaul Karim 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 2018-01-31 with Computers categories.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. Key Features Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Book Description Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. What you will learn Apply advanced regression techniques to boost the performance of predictive models Use different classification algorithms for business analytics Generate trading strategies for Bitcoin and stock trading using ensemble techniques Train Deep Neural Networks (DNN) using H2O and Spark ML Utilize NLP to build scalable machine learning models Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application Learn how to use autoencoders to develop a fraud detection application Implement LSTM and CNN models using DeepLearning4j and MXNet Who this book is for If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful.

Advanced Typescript Programming Projects

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Author : Peter O'Hanlon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-07-26

Advanced Typescript Programming Projects written by Peter O'Hanlon 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 2019-07-26 with Computers categories.

Gain in-depth knowledge of TypeScript and the latest ECMAScript standards by building robust web applications across different domains Key FeaturesApply the cutting-edge features of TypeScript 3.0 to build high-performance, maintainable applicationsLearn through practical examples of using TypeScript with popular frameworks, such as Angular and React Focus on building high-quality applications that are modular, scalable and adaptableBook Description With the demand for ever more complex websites, the need to write robust, standard-compliant JavaScript has never been greater. TypeScript is modern JavaScript with the support of a first-class type system, which makes it simpler to write complex web systems. With this book, you’ll explore core concepts and learn by building a series of websites and TypeScript apps. You’ll start with an introduction to TypeScript features that are often overlooked in other books, before moving on to creating a simple markdown parser. You’ll then explore React and get up to speed with creating a client-side contacts manager. Next, the book will help you discover the Angular framework and use the MEAN stack to create a photo gallery. Later sections will assist you in creating a GraphQL Angular Todo app and then writing a Socket.IO chatroom. The book will also lead you through developing your final Angular project which is a mapping app. As you progress, you’ll gain insights into React with Docker and microservices. You’ll even focus on how to build an image classification program with machine learning using TensorFlow. Finally, you’ll learn to combine TypeScript and C# to create an ASP.NET Core-based music library app. By the end of this book, you’ll be able to confidently use TypeScript 3.0 and different JavaScript frameworks to build high-quality apps. What you will learnDiscover how to use TypeScript to write code using common patternsGet to grips with using popular frameworks and libraries with TypeScriptLeverage the power of both server and client using TypeScriptLearn how to apply exciting new paradigms such as GraphQL and TensorFlowUse popular cloud-based authenticated servicesCombine TypeScript with C# to create ASP.NET Core applicationsWho this book is for This book is for programmers and web developers who are familiar with TypeScript and want to put their knowledge to work by building real-world complex applications. Prior experience with any other web framework is not required.

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

Advancement Of Intelligent Computational Methods And Technologies

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Author : O.P. Verma
language : en
Publisher: CRC Press
Release Date : 2024-06-30

Advancement Of Intelligent Computational Methods And Technologies written by O.P. Verma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-30 with Computers categories.

The compiled volume originates from the notable contributions presented at the 1st International Conference on Advancementof Intelligent Computational Methods and Technologies (AICMT2023), which took place in a hybrid format on June 27, 2023,at Delhi Technical Campus, Greater Noida, Uttar Pradesh, India. This comprehensive collection serves as an exploration into the dynamic domain of intelligent computational methods and technologies, offering insights into the latest and upcoming trends in computation methods. AICMT2023’s scope encompasses the evolutionary trajectory of computational methods, addressing pertinent issues in real time implementation, delving into the emergence of new intelligent technologies, exploring next-generation problem-solving methodologies, and other interconnected areas. The conference is strategically designed to spotlight current research trendswithin the field, fostering a vibrant research culture and contributing to the collective knowledge base.