Transformers have taken over computer vision—and if you’re not using them, you’re already behind . From powering self-driving cars to enabling breakthrough medical diagnostics, vision transformers are redefining what’s possible in AI. Now is your chance to master them with PyTorch and Hugging Face and bring cutting-edge deep learning into your own projects. Inside this hands-on guide, you’ll discover how to move from theory to production with confidence: Build and fine-tune pretrained Vision Transformers for state-of-the-art image classification. Implement object detection and segmentation pipelines with DETR, SAM, and more. Harness transfer learning with Hugging Face datasets for real-world efficiency. Deploy models with ONNX, TorchScript, and FastAPI to web and mobile apps. Scale your work with distributed training, quantisation, and edge deployment strategies. Written by an experienced author with a proven track record in AI and deep learning, this book balances clarity with technical depth. Every concept is backed by runnable code samples so you can learn by building—not just by reading. This book is for AI developers, data scientists, researchers, and ambitious learners who want to stay ahead of the curve in computer vision. Whether you’re entering the field or scaling production systems, the knowledge here will future-proof your skills. Don’t get left behind in the AI revolution . Equip yourself with the tools and techniques that top labs and companies are using today. Scroll up, grab your copy, and start building the next generation of vision-powered applications now.