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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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Andrej Karpathy's explaination of Bigram Language Model explained Bigram LMs, though simple, it provides powerful insight into the inner mechanics of how tokens are processed in language models. This is a pre-amble for what's next: GPT, which is the 2nd part of the series The Bigram model here incorporates: Tokenization, Vocabulary, Negative Loss Function, Cross Entropy, Logits, SoftMax, Optimizer, and AdamW These are essential ingredients to understand in order to build our knowledge on how LLM
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AI Race between open vs closed models just entered the next level. Crazy takes like calling open models decelerationist by virtue and calling open models a threat and are heading down a dangerous path are only some criticism against open models showing how much threat they pose to close labs' business model. The further commoditization of models is really pushing further pressure on frontier labs especially for some that are eyeing IPO in the next year. #artificialintelligence #openmodels #kimi
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