Scicrop/llm-vision-basics
Educational notebooks that demystify Large Language Models and Computer Vision. We build everything from scratch — from a simple bigram language model to RNNs, LSTMs, Attention, Transformers, CNNs, and Diffusion models (DDPM) — using pure Python and PyTorch. No hype. Just code.
Want to truly understand how Large Language Models (LLMs) and Computer Vision models work without the hype? These notebooks break down complex AI concepts into understandable components using pure Python and PyTorch. Starting with basic text analysis, you'll build up to sophisticated models like Transformers and Diffusion. This resource is perfect for anyone with basic Python skills who wants to demystify AI and see the engineering behind the magic.
Use this if you are an analyst, researcher, or curious professional with basic Python knowledge and want to understand the inner workings of modern AI systems like LLMs and image generators, rather than just using them as black boxes.
Not ideal if you are looking for an advanced machine learning course with deep theoretical proofs or a production-ready codebase for immediate application.
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Jupyter Notebook
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Apache-2.0
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Last pushed
Mar 25, 2026
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