Image Classification Using Vision Transformer (ViT) with Your Custom Dataset - Full Tutorial

This comprehensive tutorial video guides you through building a Vision Transformer (ViT) from scratch using PyTorch for image classification with custom datasets. Learn the complete workflow from data preparation to model deployment, including loading and transforming image datasets, creating patch embeddings, implementing Multi-Head Self-Attention mechanisms, building a Transformer Encoder for image processing, training and optimizing your ViT model, and testing with real data. Follow along with step-by-step instructions covering installation, dataset exploration, image patch creation, model building, training, and prediction. The 44-minute tutorial includes timestamps for easy navigation through each section, from introduction to final model testing. Access the complete code through the provided link and explore additional computer vision and visual language model tutorials from the creator's playlists and blog.