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Learn to build a Vision Transformer (ViT) from scratch using PyTorch! This hands-on course guides you through each component, from patch embedding to the Transformer Encoder. Train your custom ViT model on CIFAR-10 and gain practical experience in image classification. Transition from CNNs to transformers in this efficient, end-to-end tutorial.
Code:
Course developed by @programmingoceanacademy
❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning:
⭐️ Contents ⭐️
⌨️ (0:00:00) Intro
⌨️ (0:28:23) Theoretical Explanation of Vision Transformers
⌨️ (0:47:40) Environment Setup and Library Imports
⌨️ (0:55:14) Configurations and Hyperparameter Setup
⌨️ (0:58:28) Image Transformation Operations
⌨️ (1:00:28) Downloading the CIFAR-10 Dataset
⌨️ (1:04:22) Creating DataLoaders
⌨️ (1:11:32) Building the Vision Transformer (ViT) Model
⌨️ (1:43:41) Defining Loss Function and Optimizer
⌨️ (1:45:37) Training Loop and Model Training
⌨️ (2:03:18) Visualizing Accuracy (Training vs Testing)
⌨️ (2:06:08) Making and Visualizing Predictions
⌨️ (2:18:48) Fine-Tuning with Data Augmentation
⌨️ (2:25:08) Training the Fine-Tuned Model
⌨️ (2:27:08) Visualizing Fine-Tuned Accuracy
⌨️ (2:28:38) Predictions After Fine-Tuning
🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual
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Learn to co
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2025/05/27
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