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Modern Computer Vision With Pytorch 2nd Edition A Practical Roadmap From Deep Learning Fundamentals To Advanced Applications And Generative Ai 2nd V Kishore Ayyadevara

  • SKU: BELL-57653166
Modern Computer Vision With Pytorch 2nd Edition A Practical Roadmap From Deep Learning Fundamentals To Advanced Applications And Generative Ai 2nd V Kishore Ayyadevara
$ 31.00 $ 45.00 (-31%)

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Modern Computer Vision With Pytorch 2nd Edition A Practical Roadmap From Deep Learning Fundamentals To Advanced Applications And Generative Ai 2nd V Kishore Ayyadevara instant download after payment.

Publisher: Packt Publishing - ebooks Account
File Extension: PDF
File size: 53.4 MB
Pages: 747
Author: V Kishore Ayyadevara, Yeshwanth Reddy
ISBN: 9781803231334, 1803231335
Language: English
Year: 2024
Edition: 2nd

Product desciption

Modern Computer Vision With Pytorch 2nd Edition A Practical Roadmap From Deep Learning Fundamentals To Advanced Applications And Generative Ai 2nd V Kishore Ayyadevara by V Kishore Ayyadevara, Yeshwanth Reddy 9781803231334, 1803231335 instant download after payment.

Whether you are a beginner or are looking to progress in your computer vision career, this book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks.

The second edition of Modern Computer Vision with PyTorch is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion.

You’ll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you'll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You’ll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you’ll utilize foundation models' capabilities to perform zero-shot object detection and image segmentation. Finally, you’ll learn best practices for deploying a model to production.

By the end of this deep learning book, you'll confidently leverage modern NN architectures to solve real-world computer vision problems.

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