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3 AI Projects That Can Actually Make Your GitHub Portfolio STAND OUT in 2026 🚀 If you’re learning AI Engineering, Machine Learning, Generative AI or LLMs and wondering “What projects should I build to get a job?” start here. 👇 In this video, I break down 3 job-ready AI projects that you can build and showcase on your GitHub portfolio. You’ll learn: ✅ What to build ✅ Why each project matters ✅ Which AI/ML skills it demonstrates ✅ How to structure the project ✅ What to add to your GitHub README
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Nobody ever wrote the code that lets ChatGPT write Python. Not one line of it. 🤯 Here's how a large language model actually gets built, step by step: 1️⃣ Data. Trillions of words of books, web pages, code and forums, then cleaned: duplicates removed, spam filtered, broken text stripped. One open dataset, FineWeb, is 15 trillion tokens of web text. 2️⃣ Tokens. The model never sees words.
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The model isn’t the entire AI system. Everything is becoming a plugin. Search? Plug it in. Code execution? Plug it in. Memory, retrieval, validation, specialized tools, or even a better model? Swap them in without rebuilding everything. The harness is the real control layer. It decides what gets called, when it gets called, what context it receives, and where the result goes next. The future of AI products may not belong to whoever owns one perfect model. It may belong to whoever builds the best
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