Vision Transformer from Scratch Tutorial

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 ❤️ Try interactive Python courses we love, right in your browser: https://scrimba.com/freeCodeCamp-Python (Made possible by a grant from our friends at Scrimba)

⭐️ 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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