raimbekovm/cs231n-2025-notes
📚 Comprehensive lecture notes for Stanford CS231n: Deep Learning for Computer Vision (2025 Edition) — CNNs, Transformers, Diffusion Models, Vision-Language Models
These notes provide a comprehensive study guide for Stanford's CS231n Deep Learning for Computer Vision course, updated for 2025. They take complex topics like CNNs, Transformers, and Diffusion Models and present them with clear explanations, mathematical details, and visual aids. This is for anyone looking to learn or review cutting-edge computer vision techniques.
Use this if you are a student, researcher, or practitioner in AI/ML needing an up-to-date and detailed resource to understand deep learning concepts specifically for computer vision.
Not ideal if you are looking for a basic introduction to machine learning or a course on general deep learning without a focus on vision.
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Jan 24, 2026
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