Vision Transformers (ViTs) are reshaping computer vision by bringing the power of self-attention to image processing. In this tutorial you will learn how to build a Vision Transformer from scratch. By the end of the course, you'll have a deeper understanding of how AI models process visual data.
Course developed by @tungabayrak9765.
💻 Code: https://colab.research.google.com/drive/1Q6bfCG5UZ7ypBWft9auptcD4Pz5zQQQb?usp=sharing#scrollTo=1EaWO-aNOk3v
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⭐️ Contents ⭐️
(0:00:00) Intro to Vision Transformer
(0:03:48) CLIP Model
(0:08:16) SigLIP vs CLIP
(0:12:09) Image Preprocessing
(0:15:32) Patch Embeddings
(0:20:48) Position Embeddings
(0:23:51) Embeddings Visualization
(0:26:11) Embeddings Implementation
(0:32:03) Multi-Head Attention
(0:46:19) MLP Layers
(0:49:18) Assembling the Full Vision Transformer
(0:59:36) Recap
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