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Deep Learning for Computer Vision with PyTorch: Create Powerful AI Solutions, Accelerate Production, and Stay Ahead with Transformers and Diffusion Mo

by William L. Younker
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Current price ₹1,667.00
Original price ₹1,871.00
Original price ₹1,871.00
Original price ₹1,871.00
(-11%)
₹1,667.00
Current price ₹1,667.00

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Book cover type: Paperback
  • ISBN13: 9798264710391
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 116
  • Original Price: GBP 14.79
  • Language: English
  • Edition: N/A
  • Item Weight: 214 grams
  • BISAC Subject(s): Languages / Python

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 tools

  • Harnessing CNNs, Vision Transformers (ViT), and generative diffusion models for image classification, detection, segmentation, and creative tasks

  • Leveraging transfer learning for rapid prototyping and instant accuracy boosts

  • Optimizing and deploying robust models with TorchScript, TorchServe, and Docker

  • Integrating monitoring, drift detection, and reproducibility practices that set your production systems apart

  • Navigating real-world challenges-data imbalance, bias, privacy, adversarial testing, and ethical deployment

You'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.

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