Mastering AI App Development with MERN Stack: Step into the Future of App Development by Building Intelligent AI-Powered Applications with MERN Stack ... Stack Web Developer — MERN & Next.js Path) - Softcover

Acharjee, Anik; AVA, Orange

Softcover

ISBN 10: 9348107682 ISBN 13: 9789348107688

Publisher: Orange Education Pvt. Ltd, 2024

Synopsis

Transform Your Web App Development Journey with MERN and AI

Are you ready to step confidently into the next era of web development? Mastering AI App Development with MERN Stack is your complete hands-on guide to building intelligent, data-driven applications using AI app development with MERN stack, full-stack JavaScript, and TensorFlow.js for developers.

Book Description
With 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.

What You’ll Learn:

• Foundations of artificial intelligence web development and how to embed intelligent features with MERN stack and JavaScript machine learning
• End-to-end walkthroughs on building intelligent AI-powered web applications using Node.js, Express.js, React intelligent interfaces, and MongoDB for AI projects
• Step-by-step tutorials for real-world MERN stack AI book applications, including creating Node.js AI chatbots, image recognition, and recommendation systems
• How to seamlessly connect TensorFlow.js for web development and machine learning JavaScript with MERN stack projects
• Deployment insights for scalable MERN AI applications—from security and best practices to real user personalization
• Integrating data-driven features.

Who Is This Book For?

• Developers and students eager to unlock cutting-edge full-stack development guide knowledge for web application AI
• Tech professionals seeking proven strategies in artificial intelligence web development and MERN stack machine learning
• Entrepreneurs and product builders wanting to add intelligent app development and personalized user experience to their solutions

Your Roadmap to AI-Powered Success:

• Build real-world machine learning with MERN stack projects using clear, step-by-step guidance
• Develop personalized user experience with AI integration and recommendation systems
• Gain actionable skills for secure and scalable MERN stack AI deployment and data-driven business value.

Create the Next Generation of AI-Powered Applications!

Table of Contents
1. Introduction to AI and the MERN Ecosystem
2. Setting Up the MERN Development Environment
3. Fundamentals of Machine Learning with JavaScript
4. Implementing AI with Node.js and TensorFlow.js
5. Creating Intelligent User Interfaces with React
6. Data Management for AI with MongoDB
7. Building AI Middleware with Express.js
8. Crafting AI-Powered Chatbots
9. Image and Voice Recognition Capabilities
10. Personalization with Recommendation Systems
11. Deploying MERN and AI Applications
12. Security Practices for AI-Enabled MERN Applications
13. Scaling AI Features in Production
14. Emerging Trends in AI and MERN Development
15. Case Studies and Real-World Success Stories
Index

Edition details

• Publisher: Orange Education Pvt. Ltd
• Publication date: 2024
• Language: English
• ISBN 10: 9348107682
• ISBN 13: 9789348107688
• Binding: Paperback
• Number of pages: 436