Hi, my name is Zain Abo Almagd
I'm the Developer you need.

🚀 Background Generator Website: Designed and built a dynamic tool for creating custom backgrounds using HTML, CSS, Bootstrap, and JavaScript.
Utilized DOM manipulation for real-time updates.
Overcame challenges by debugging JS logic and enhancing UI with Bootstrap, showcasing problem-solving and a user-focused approach. 🌟

Robo Friends is a React app displaying a searchable gallery of robot avatars.
During development, I faced two key challenges:
Build Error (OSSL Unsupported): Solved by downgrading Node.js to v18.x and updating react-scripts.
Deployment Error (ENAMETOOLONG): Fixed by modifying the gh-pages package to process arguments in smaller chunks.
The app features responsive design, gradient backgrounds, and a smooth search experience, showcasing my problem-solving skills and React expertise.

Features :

• Functionality: Users can search for their favorite robots by typing in their names.
• Responsive Design: The app works seamlessly on both desktop and mobile devices.
• Customizable Backgrounds: I used gradient colors to create a visually appealing interface.

A full-stack web application built using React for the frontend and Node.js for the backend. It utilizes the Clarifai Face Detection Model to analyze images and detect faces. The backend is powered by Express.js and stores user data and detection history in a PostgreSQL database. This project demonstrates my ability to integrate third-party APIs, manage a robust backend, and build an interactive and responsive frontend.

Technologies Used

• Frontend: React.js, tsparticles/react (for UI enhancements), Tailwind CSS
• Backend: Node.js, Express.js
• Database: PostgreSQL
• API Integration: Clarifai Face Detection Model
• Authentication: User login and registration with hashed passwords

Challenges and Solutions

1. Managing CORS Issues

Obstacle: While connecting the frontend and backend, I encountered CORS (Cross-Origin Resource Sharing) errors.

Solution: Used the cors package in Node.js and configured it properly to allow only the necessary origins to access the backend.

2. Database Setup & Queries

Obstacle: Writing efficient queries for user authentication and tracking face detection history in PostgreSQL required optimization.

Solution: Implemented Knex.js as a query builder, indexed frequently accessed data, and optimized database queries to enhance performance.

3. Frontend Performance & UI Enhancements

Obstacle: Rendering large images and multiple face detections slowed down the UI.

Solution: Used React’s useEffect for efficient state updates and implemented lazy loading for images to improve performance.

Key Takeaways

• Successfully built a full-stack application integrating AI-powered face detection.
• Strengthened my ability to solve backend integration challenges.
• Improved performance optimizations in React and PostgreSQL.
• Learned best practices for API security and deployment strategies.

This project was a great learning experience, refining my skills in full-stack development, API integration, and problem-solving.