Building a Strong AI/ML Portfolio: GitHub, Kaggle, and Beyond

Your portfolio is your ticket to landing interviews. Here's how to build one that stands out. ## GitHub Projects (Most Important) 1. **Quality over quantity**: 3 great projects > 10 mediocre ones 2. **Document obsessively**: README, architecture diagrams, results 3. **Show production awareness**: Docker, CI/CD, testing Example project ideas: - Fine-tuned LLM for specific domain - Real-time object detection system - End-to-end ML pipeline with monitoring ## Kaggle Competitions - Aim for at least one Silver medal - Document your approach in a kernel - Shows you can compete with peers ## Open Source Contributions - Contribute to popular ML libraries - Fix bugs, improve documentation - Shows collaboration skills ## Blogging - Write about your projects on Medium or personal blog - Explain complex concepts simply - Demonstrates communication skills