Deep learning computer vision de younker william (9 resultados)
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Paperback. Condición: new. Paperback. Deep Learning for Computer Vision with PyTorch: Create Powerful AI Solutions, Accelerate Production, and Stay Ahead with Transformers and Diffusion Models Can you turn raw images into business insights, creative breakthroughs, or the next industry-standard product?Today's computer vision is…more than algorithms-it's the foundation for innovation in every field, from healthcare and finance to entertainment and AI-powered apps. Yet, with so many rapid advances, even experienced developers face a crucial question: How do you build, scale, and ship state-of-the-art vision solutions that actually work in the real world?Deep Learning for Computer Vision with PyTorch puts the latest breakthroughs-Vision Transformers, diffusion models, transfer learning, and production-ready pipelines-directly into your hands. This book is designed for engineers, data scientists, and forward-thinking developers who want practical, code-driven answers and results you can trust.Master every essential skill, including: Constructing high-performance vision pipelines with PyTorch 2.x, TorchVision, and powerful augmentation toolsHarnessing CNNs, Vision Transformers (ViT), and generative diffusion models for image classification, detection, segmentation, and creative tasksLeveraging transfer learning for rapid prototyping and instant accuracy boostsOptimizing and deploying robust models with TorchScript, TorchServe, and DockerIntegrating monitoring, drift detection, and reproducibility practices that set your production systems apartNavigating real-world challenges-data imbalance, bias, privacy, adversarial testing, and ethical deploymentYou'll build hands-on projects from scratch to scalable API services, with every chapter anchored in code you can run, extend, and use today. This is your guide to staying ahead-whether you're automating workflows, shipping cloud apps, or inventing new creative tools. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Paperback. Condición: new. Paperback. Deep Learning for Computer Vision with PyTorch: Create Powerful AI Solutions, Accelerate Production, and Stay Ahead with Transformers and Diffusion Models Can you turn raw images into business insights, creative breakthroughs, or the next industry-standard product?Today's computer vision is…more than algorithms-it's the foundation for innovation in every field, from healthcare and finance to entertainment and AI-powered apps. Yet, with so many rapid advances, even experienced developers face a crucial question: How do you build, scale, and ship state-of-the-art vision solutions that actually work in the real world?Deep Learning for Computer Vision with PyTorch puts the latest breakthroughs-Vision Transformers, diffusion models, transfer learning, and production-ready pipelines-directly into your hands. This book is designed for engineers, data scientists, and forward-thinking developers who want practical, code-driven answers and results you can trust.Master every essential skill, including: Constructing high-performance vision pipelines with PyTorch 2.x, TorchVision, and powerful augmentation toolsHarnessing CNNs, Vision Transformers (ViT), and generative diffusion models for image classification, detection, segmentation, and creative tasksLeveraging transfer learning for rapid prototyping and instant accuracy boostsOptimizing and deploying robust models with TorchScript, TorchServe, and DockerIntegrating monitoring, drift detection, and reproducibility practices that set your production systems apartNavigating real-world challenges-data imbalance, bias, privacy, adversarial testing, and ethical deploymentYou'll build hands-on projects from scratch to scalable API services, with every chapter anchored in code you can run, extend, and use today. This is your guide to staying ahead-whether you're automating workflows, shipping cloud apps, or inventing new creative tools. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
