Vision Transformers from Scratch: How Treating Images as Sentences Changed Computer Vision
We break down the Vision Transformer (ViT) paper step by step — from image patches to self-attention — with intuition, math, and a full PyTorch implementation.
beginner~7 hours3 notebooksThe Big Idea: Reading Images Like SentencesA Quick Refresher: Why CNNs Were KingThe Core Idea: Images as Sequences of PatchesPatch Embedding and Position EmbeddingThe Transformer Encoder: Self-Attention on Patches
Curator of this Module
Dr. Rajat Dandekar
Course Instructor
Dr. Rajat Dandekar is a researcher and educator specializing in AI/ML, with a passion for making complex concepts accessible through intuitive explanations and hands-on learning.
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Learning Path
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Notebook 23
Notebook 3Case Study
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