- HTML
Nice to meet you!
I'm Michael Dawson
👋 Hi, I’m Michael Dawson — a frontend developer based in the UK who enjoys building fast, accessible web apps. I’ve built full-stack projects using JavaScript, React, and Node.js, and recently completed a remote internship where I contributed production-ready features using Next.js, Prisma, and Stripe. I focus on clean UI, responsiveness, and real-world problem solving.
- CSS
- BOOTSTRAP
- JAVASCRIPT
- JQUERY
- REACT
- MONGODB
- NODEJS
My Projects
- Product Finder
- Product Finder is a web application that allows users to search for better online prices of a product by uploading an image. The app uses Google Vision API to identify visually similar items and a Real-Time Product Search API to retrieve live product data and pricing. The frontend was built with React. The project originally began as a group capstone project during a Frontend Developer Bootcamp. My initial contributions included implementing image upload support for multiple formats (PNG, SVG, and HEIC using heic2any), integrating the Google Vision API, and connecting the Real-Time Product Search API to return live results. I later forked the project and took full ownership to improve security, performance, and deployment. API keys were previously exposed on the client, so I refactored the architecture and implemented a serverless deployment using Netlify Functions to securely handle API requests. I also added more robust error handling, improved responsiveness across devices, refined the UI/UX, and worked on improving result accuracy from the Vision API. The application is now fully deployed serverlessly on Netlify, with secure API handling and a more polished, responsive user experience. Future improvements include further enhancing mobile responsiveness and improving image recognition accuracy, which would likely require training custom models for cases where Google Vision does not return reliable labels.
- Restaurant Tracker
- Restaurant Tracker is an application that lets users explore restaurants in London with interactive maps and search features. Users can search by name or type of cuisine. My contributions: Added interactive markers on the Mapbox map to show restaurant locations, implemented cuisine-based search to filter restaurants by type, built a search form to allow users to find restaurants by name or keyword, and integrated the Local Business Data API to fetch up-to-date restaurant information.
- Product Feedback App
- Product Feedback App is a full-stack application that allows users to submit product suggestions, comment on others’ suggestions, reply to comments, and upvote ideas. The app is built with Node.js, Express, MongoDB, and the Cloudinary API, with a login and registration system to manage user authentication. The project began as a Frontend Mentor Guru-level challenge, which originally used static JSON data. My contributions included replacing the JSON with a MongoDB database for scalability, implementing user authentication, and integrating Cloudinary for media handling. I also improved data relationships to support comments and replies in a structured way, ensuring a seamless user experience. The application is now fully functional with persistent data storage, secure user authentication, and dynamic interaction between users. Future improvements could include adding real-time updates with WebSockets, enhanced analytics for user suggestions, and improved UI/UX for better accessibility across devices.