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Isaac Mwesigwa - Developer Portfolio

Portfolio Website GitHub LinkedIn

Welcome to my personal portfolio website! This is a modern, interactive showcase of my projects, skills, and professional experience as a Full Stack Developer and Machine Learning Enthusiast.

Features

  • Responsive Design: Fully optimized for desktop, tablet, and mobile devices
  • Interactive UI: Smooth animations, 3D card effects, and dynamic hover states
  • Modern Aesthetics: Clean, professional design with gradient accents and dark theme
  • Performance Optimized: Fast loading times with optimized assets and efficient code
  • Accessibility: Semantic HTML and keyboard-navigable interface

Technologies Used

Frontend

  • HTML5: Semantic markup for better accessibility
  • CSS3: Modern styling with CSS Grid, Flexbox, and custom properties
  • JavaScript (ES6+): Interactive features and animations
  • SVG: Scalable vector icons for crisp visuals

Design Features

  • Custom CSS animations and transitions
  • 3D tilt effects on cards
  • Parallax scrolling effects
  • Cursor trail animation
  • Scroll progress indicator
  • Dynamic gradient backgrounds
  • Intersection Observer API for scroll animations

Key Sections

Hero Section

  • Eye-catching introduction with animated profile picture
  • Gradient text effects
  • Quick links to GitHub, LinkedIn, and contact information

Featured Projects

  • Highlighted projects with detailed descriptions
  • Technology tags for quick reference
  • Direct links to live demos and repositories

Skills & Technologies

  • Organized by category (Languages, Web Dev, ML, Tools, Databases)
  • Interactive hover effects
  • Comprehensive overview of technical expertise

Contact

  • Multiple ways to get in touch
  • Professional social media links
  • Email contact with beautiful icons

💡 Highlighted Projects

Football Player Recognition

Advanced machine learning model trained on 42,000+ images from the 2022 World Cup, using microsoft/resnet-18 architecture with deployed inference API.

ML Projects

Comprehensive collection of machine learning implementations from Stanford University's ML course, demonstrating practical applications of core concepts.

JavaScript Projects

Modern full-stack applications built with vanilla JavaScript, Vue 3, and Node.js, showcasing contemporary web development practices.

License

This project is open source and available for educational purposes. Feel free to fork and customize for your own portfolio!

📧 Contact

Acknowledgments

  • Icons: Custom SVG designs
  • Fonts: System font stack for optimal performance
  • Color Palette: Custom gradient-based design system

Built with ❤️ by Isaac Mwesigwa | Last Updated: January 2026

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